601 lines
19 KiB
JavaScript
601 lines
19 KiB
JavaScript
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{
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"translatorID": "f4a5876a-3e53-40e2-9032-d99a30d7a6fc",
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"label": "ACLWeb",
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"creator": "Guy Aglionby",
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"target": "^https?://(www\\.)?(aclanthology\\.org|aclweb\\.org/anthology)/",
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"minVersion": "3.0",
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"maxVersion": "",
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"priority": 100,
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"inRepository": true,
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"translatorType": 4,
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"browserSupport": "gcsibv",
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"lastUpdated": "2022-11-10 10:36:48"
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}
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/*
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***** BEGIN LICENSE BLOCK *****
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Copyright © 2018 Guy Aglionby
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This file is part of Zotero.
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Zotero is free software: you can redistribute it and/or modify
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it under the terms of the GNU Affero General Public License as published by
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the Free Software Foundation, either version 3 of the License, or
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(at your option) any later version.
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Zotero is distributed in the hope that it will be useful,
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but WITHOUT ANY WARRANTY; without even the implied warranty of
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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GNU Affero General Public License for more details.
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You should have received a copy of the GNU Affero General Public License
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along with Zotero. If not, see <http://www.gnu.org/licenses/>.
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***** END LICENSE BLOCK *****
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*/
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var ext2mime = {
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gz: 'application/gzip',
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tgz: 'application/gzip',
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pdf: 'application/pdf',
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zip: 'application/zip',
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tar: 'application/x-tar',
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txt: 'text/plain',
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rar: 'application/x-rar-compressed',
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rtf: 'application/rtf',
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bz2: 'application/x-bzip2',
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bz: 'application/x-bzip',
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doc: 'application/msword',
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docx: 'application/vnd.openxmlformats-officedocument.wordprocessingml.document',
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ppt: 'application/vnd.ms-powerpoint',
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pptx: 'application/vnd.openxmlformats-officedocument.presentationml.presentation',
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xls: 'application/vnd.ms-excel',
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xlsx: 'application/vnd.openxmlformats-officedocument.spreadsheetml.sheet',
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html: 'text/html',
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png: 'image/png',
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gif: 'image/gif',
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jpg: 'image/jpeg',
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jpeg: 'image/jpeg',
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mp4: 'video/mp4',
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tsv: 'text/tab-separated-values',
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csv: 'text/csv',
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py: 'text/x-python',
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tex: 'text/x-tex',
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bbl: 'text/x-tex'
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};
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function detectWeb(doc, url) {
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let paperIdRegex = /([A-Z])\d{2}-\d{4}|\d{4}\.([\w\d]+)-[\w\d]+\.\d+/;
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let paperMatch = url.match(paperIdRegex);
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if (paperMatch) {
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let venue = paperMatch[1] ? paperMatch[1] : paperMatch[2];
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venue = venue.toLowerCase();
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if (venue == 'j' || venue == 'q' || venue == 'tacl' || venue == 'cl') {
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return 'journalArticle';
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}
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else {
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return 'conferencePaper';
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}
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}
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else if ((url.includes('/events/') || url.includes('/people/')
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|| url.includes('/volumes/') || url.includes('/search/'))
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&& getSearchResults(doc, url)) {
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return 'multiple';
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}
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return false;
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}
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function doWeb(doc, url) {
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if (detectWeb(doc, url) === 'multiple') {
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Zotero.selectItems(getSearchResults(doc, url), function (selected) {
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if (selected) {
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ZU.processDocuments(Object.keys(selected), scrape);
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}
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});
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}
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else if (url.endsWith('.bib')) {
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let paperURL = url.slice(0, -'.bib'.length);
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ZU.processDocuments(paperURL, scrape);
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}
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else if (url.endsWith('.pdf')) {
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// e.g. http://aclweb.org/anthology/P18-1001.pdf
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let paperURL = url.slice(0, -'.pdf'.length);
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ZU.processDocuments(paperURL, scrape);
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}
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else {
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scrape(doc);
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}
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}
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function scrape(doc) {
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let bibtex = ZU.xpath(doc, '//pre[@id = "citeBibtexContent"]')[0].textContent;
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let pdfURL = ZU.xpath(doc, '//a[span[contains(text(), "PDF")]]/@href')[0].value;
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let translator = Zotero.loadTranslator("import");
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translator.setTranslator("9cb70025-a888-4a29-a210-93ec52da40d4");
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translator.setString(bibtex);
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translator.setHandler("itemDone", function (obj, item) {
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item.attachments.push({
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url: pdfURL,
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title: 'Full Text PDF',
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mimeType: 'application/pdf'
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});
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delete item.itemID;
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if (item.date) {
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item.date = ZU.strToISO(item.date);
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}
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if (item.abstractNote) {
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item.abstractNote = ZU.cleanTags(item.abstractNote);
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}
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if (item.itemType == 'conferencePaper') {
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item.conferenceName = getVenue(doc, item.publicationTitle);
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}
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if (Z.getHiddenPref('attachSupplementary')) {
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let supplementaries = ZU.xpath(doc, '//div[contains(@class, "acl-paper-link-block")]//a[contains(@class, "btn-attachment")]');
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supplementaries.forEach(function (supplementary) {
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let ext = supplementary.href.split('.').pop();
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let supplementaryMime = Z.getHiddenPref('supplementaryAsLink') ? 'text/html' : ext2mime[ext];
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item.attachments.push({
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url: supplementary.href,
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title: supplementary.text,
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mimeType: supplementaryMime || 'text/html',
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snapshot: !Z.getHiddenPref('supplementaryAsLink')
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});
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});
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}
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item.complete();
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});
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translator.translate();
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}
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function getVenue(doc, pubTitle) {
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let venueElements = ZU.xpath(doc, '//dt[contains(text(), "Venue")]//following::dd[1]/a');
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let venues = venueElements.map(function (v) {
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return v.innerText.trim();
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});
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if (!venues.length) {
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return '';
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}
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let year = ZU.xpath(doc, '//dt[contains(text(), "Year")]/following::dd[1]')[0].textContent;
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let venueString = venues.join('-') + ' ' + year;
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if (pubTitle.includes('Student') || pubTitle.includes('Demonstration') || pubTitle.includes('Tutorial')) {
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// better to use full proceedingsTitle to cite these publications
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return '';
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}
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if (venueString.includes('SemEval')) {
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if (pubTitle.includes('SENSEVAL')) {
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return 'SENSEVAL ' + year;
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}
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else if (pubTitle.includes('Evaluation') && !pubTitle.includes('Joint')) {
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return 'SemEval ' + year;
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}
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else if (!pubTitle.includes('Evaluation') && pubTitle.includes('Joint')) {
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return '*SEM ' + year;
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}
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else if (pubTitle.includes('Volume 1') && pubTitle.includes('Volume 2')) {
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return '*SEM/SemEval ' + year;
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}
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else if (pubTitle.includes('SemEval')) {
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return 'SemEval ' + year;
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}
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else {
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return '*SEM ' + year;
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}
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}
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else if (venueString.includes('WS')) {
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// better to use full proceedingsTitle to cite these publications
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return '';
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}
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else if (!venueString.includes("HLT") && pubTitle.match('HLT|Human Language Technolog(y|ies)')) {
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return venues.join('-') + '-HLT ' + year;
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}
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return venueString;
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}
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function getSearchResults(doc, url) {
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let items = {};
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if (url.includes('/search/')) {
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// e.g. https://www.aclweb.org/anthology/search/?q=foo+bar
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let results = ZU.xpath(doc, '//div[contains(@class, "gsc-webResult")]//div[contains(@class, "gs-title")]/a');
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let paperRegex = /[A-Z]\d{2}-\d{4}|\d{4}\.[\w\d]+-[\w\d]+\.\d+/;
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for (let result of results) {
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let url = result.href;
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if (url.match(paperRegex)) {
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if (url.endsWith('.pdf')) {
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url = url.slice(0, -'.pdf'.length);
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}
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items[url] = result.text;
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}
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|||
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}
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}
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|||
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else {
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let papers = ZU.xpath(doc, '//section[@id="main"]//strong/a');
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for (let paper of papers) {
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items[paper.href] = paper.text;
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}
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|||
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}
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return Object.keys(items).length ? items : false;
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|||
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}
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|||
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/** BEGIN TEST CASES **/
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var testCases = [
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{
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"type": "web",
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"url": "https://www.aclanthology.org/events/acl-2018/",
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"items": "multiple"
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},
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{
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"type": "web",
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"url": "https://www.aclanthology.org/volumes/P18-1/",
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"items": "multiple"
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},
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{
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"type": "web",
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"url": "https://www.aclanthology.org/people/i/iryna-gurevych/",
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"items": "multiple"
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},
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{
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"type": "web",
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"url": "https://www.aclanthology.org/Q18-1001/",
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"items": [
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{
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"itemType": "journalArticle",
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"title": "Whodunnit? Crime Drama as a Case for Natural Language Understanding",
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"creators": [
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{
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"firstName": "Lea",
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"lastName": "Frermann",
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"creatorType": "author"
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},
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{
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"firstName": "Shay B.",
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"lastName": "Cohen",
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"creatorType": "author"
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},
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{
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"firstName": "Mirella",
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"lastName": "Lapata",
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"creatorType": "author"
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}
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],
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"date": "2018",
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"DOI": "10.1162/tacl_a_00001",
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"abstractNote": "In this paper we argue that crime drama exemplified in television programs such as CSI: Crime Scene Investigation is an ideal testbed for approximating real-world natural language understanding and the complex inferences associated with it. We propose to treat crime drama as a new inference task, capitalizing on the fact that each episode poses the same basic question (i.e., who committed the crime) and naturally provides the answer when the perpetrator is revealed. We develop a new dataset based on CSI episodes, formalize perpetrator identification as a sequence labeling problem, and develop an LSTM-based model which learns from multi-modal data. Experimental results show that an incremental inference strategy is key to making accurate guesses as well as learning from representations fusing textual, visual, and acoustic input.",
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"libraryCatalog": "ACLWeb",
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"pages": "1–15",
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"publicationTitle": "Transactions of the Association for Computational Linguistics",
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"shortTitle": "Whodunnit?",
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"url": "https://www.aclweb.org/anthology/Q18-1001",
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"volume": "6",
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"attachments": [
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{
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"title": "Full Text PDF",
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"mimeType": "application/pdf"
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}
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],
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"tags": [],
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"notes": [],
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"seeAlso": []
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}
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]
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},
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{
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"type": "web",
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"url": "https://www.aclanthology.org/W04-0801/",
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"items": [
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{
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"itemType": "conferencePaper",
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"title": "The Basque lexical-sample task",
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"creators": [
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{
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"firstName": "Eneko",
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"lastName": "Agirre",
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"creatorType": "author"
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},
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{
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"firstName": "Itziar",
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"lastName": "Aldabe",
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"creatorType": "author"
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},
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{
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"firstName": "Mikel",
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"lastName": "Lersundi",
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"creatorType": "author"
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},
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{
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"firstName": "David",
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"lastName": "Martínez",
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"creatorType": "author"
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},
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{
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"firstName": "Eli",
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"lastName": "Pociello",
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"creatorType": "author"
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},
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{
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"firstName": "Larraitz",
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"lastName": "Uria",
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"creatorType": "author"
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}
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],
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"date": "2004-07",
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"conferenceName": "SENSEVAL 2004",
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"libraryCatalog": "ACLWeb",
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"pages": "1–4",
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"place": "Barcelona, Spain",
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"proceedingsTitle": "Proceedings of SENSEVAL-3, the Third International Workshop on the Evaluation of Systems for the Semantic Analysis of Text",
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"publisher": "Association for Computational Linguistics",
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"url": "https://www.aclweb.org/anthology/W04-0801",
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"attachments": [
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{
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|||
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"title": "Full Text PDF",
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|||
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"mimeType": "application/pdf"
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|||
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}
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|||
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],
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"tags": [],
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"notes": [],
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"seeAlso": []
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}
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]
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},
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|||
|
|
{
|
|||
|
|
"type": "web",
|
|||
|
|
"url": "https://www.aclanthology.org/W19-0101/",
|
|||
|
|
"items": [
|
|||
|
|
{
|
|||
|
|
"itemType": "conferencePaper",
|
|||
|
|
"title": "Can Entropy Explain Successor Surprisal Effects in Reading?",
|
|||
|
|
"creators": [
|
|||
|
|
{
|
|||
|
|
"firstName": "Marten",
|
|||
|
|
"lastName": "van Schijndel",
|
|||
|
|
"creatorType": "author"
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"firstName": "Tal",
|
|||
|
|
"lastName": "Linzen",
|
|||
|
|
"creatorType": "author"
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"date": "2019",
|
|||
|
|
"DOI": "10.7275/qtbb-9d05",
|
|||
|
|
"libraryCatalog": "ACLWeb",
|
|||
|
|
"pages": "1–7",
|
|||
|
|
"proceedingsTitle": "Proceedings of the Society for Computation in Linguistics (SCiL) 2019",
|
|||
|
|
"url": "https://www.aclweb.org/anthology/W19-0101",
|
|||
|
|
"attachments": [
|
|||
|
|
{
|
|||
|
|
"title": "Full Text PDF",
|
|||
|
|
"mimeType": "application/pdf"
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"tags": [],
|
|||
|
|
"notes": [],
|
|||
|
|
"seeAlso": []
|
|||
|
|
}
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"type": "web",
|
|||
|
|
"url": "https://www.aclanthology.org/N12-2001/",
|
|||
|
|
"items": [
|
|||
|
|
{
|
|||
|
|
"itemType": "conferencePaper",
|
|||
|
|
"title": "Finding the Right Supervisor: Expert-Finding in a University Domain",
|
|||
|
|
"creators": [
|
|||
|
|
{
|
|||
|
|
"firstName": "Fawaz",
|
|||
|
|
"lastName": "Alarfaj",
|
|||
|
|
"creatorType": "author"
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"firstName": "Udo",
|
|||
|
|
"lastName": "Kruschwitz",
|
|||
|
|
"creatorType": "author"
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"firstName": "David",
|
|||
|
|
"lastName": "Hunter",
|
|||
|
|
"creatorType": "author"
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"firstName": "Chris",
|
|||
|
|
"lastName": "Fox",
|
|||
|
|
"creatorType": "author"
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"date": "2012-06",
|
|||
|
|
"libraryCatalog": "ACLWeb",
|
|||
|
|
"pages": "1–6",
|
|||
|
|
"place": "Montréal, Canada",
|
|||
|
|
"proceedingsTitle": "Proceedings of the NAACL HLT 2012 Student Research Workshop",
|
|||
|
|
"publisher": "Association for Computational Linguistics",
|
|||
|
|
"shortTitle": "Finding the Right Supervisor",
|
|||
|
|
"url": "https://www.aclweb.org/anthology/N12-2001",
|
|||
|
|
"attachments": [
|
|||
|
|
{
|
|||
|
|
"title": "Full Text PDF",
|
|||
|
|
"mimeType": "application/pdf"
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"tags": [],
|
|||
|
|
"notes": [],
|
|||
|
|
"seeAlso": []
|
|||
|
|
}
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"type": "web",
|
|||
|
|
"url": "https://www.aclanthology.org/N18-1001/",
|
|||
|
|
"items": [
|
|||
|
|
{
|
|||
|
|
"itemType": "conferencePaper",
|
|||
|
|
"title": "Label-Aware Double Transfer Learning for Cross-Specialty Medical Named Entity Recognition",
|
|||
|
|
"creators": [
|
|||
|
|
{
|
|||
|
|
"firstName": "Zhenghui",
|
|||
|
|
"lastName": "Wang",
|
|||
|
|
"creatorType": "author"
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"firstName": "Yanru",
|
|||
|
|
"lastName": "Qu",
|
|||
|
|
"creatorType": "author"
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"firstName": "Liheng",
|
|||
|
|
"lastName": "Chen",
|
|||
|
|
"creatorType": "author"
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"firstName": "Jian",
|
|||
|
|
"lastName": "Shen",
|
|||
|
|
"creatorType": "author"
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"firstName": "Weinan",
|
|||
|
|
"lastName": "Zhang",
|
|||
|
|
"creatorType": "author"
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"firstName": "Shaodian",
|
|||
|
|
"lastName": "Zhang",
|
|||
|
|
"creatorType": "author"
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"firstName": "Yimei",
|
|||
|
|
"lastName": "Gao",
|
|||
|
|
"creatorType": "author"
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"firstName": "Gen",
|
|||
|
|
"lastName": "Gu",
|
|||
|
|
"creatorType": "author"
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"firstName": "Ken",
|
|||
|
|
"lastName": "Chen",
|
|||
|
|
"creatorType": "author"
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"firstName": "Yong",
|
|||
|
|
"lastName": "Yu",
|
|||
|
|
"creatorType": "author"
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"date": "2018-06",
|
|||
|
|
"DOI": "10.18653/v1/N18-1001",
|
|||
|
|
"abstractNote": "We study the problem of named entity recognition (NER) from electronic medical records, which is one of the most fundamental and critical problems for medical text mining. Medical records which are written by clinicians from different specialties usually contain quite different terminologies and writing styles. The difference of specialties and the cost of human annotation makes it particularly difficult to train a universal medical NER system. In this paper, we propose a label-aware double transfer learning framework (La-DTL) for cross-specialty NER, so that a medical NER system designed for one specialty could be conveniently applied to another one with minimal annotation efforts. The transferability is guaranteed by two components: (i) we propose label-aware MMD for feature representation transfer, and (ii) we perform parameter transfer with a theoretical upper bound which is also label aware. We conduct extensive experiments on 12 cross-specialty NER tasks. The experimental results demonstrate that La-DTL provides consistent accuracy improvement over strong baselines. Besides, the promising experimental results on non-medical NER scenarios indicate that La-DTL is potential to be seamlessly adapted to a wide range of NER tasks.",
|
|||
|
|
"conferenceName": "NAACL-HLT 2018",
|
|||
|
|
"libraryCatalog": "ACLWeb",
|
|||
|
|
"pages": "1–15",
|
|||
|
|
"place": "New Orleans, Louisiana",
|
|||
|
|
"proceedingsTitle": "Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers)",
|
|||
|
|
"publisher": "Association for Computational Linguistics",
|
|||
|
|
"url": "https://www.aclweb.org/anthology/N18-1001",
|
|||
|
|
"attachments": [
|
|||
|
|
{
|
|||
|
|
"title": "Full Text PDF",
|
|||
|
|
"mimeType": "application/pdf"
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"tags": [],
|
|||
|
|
"notes": [],
|
|||
|
|
"seeAlso": []
|
|||
|
|
}
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"type": "web",
|
|||
|
|
"url": "https://www.aclanthology.org/2020.lrec-1.2/",
|
|||
|
|
"items": [
|
|||
|
|
{
|
|||
|
|
"itemType": "conferencePaper",
|
|||
|
|
"title": "A Cluster Ranking Model for Full Anaphora Resolution",
|
|||
|
|
"creators": [
|
|||
|
|
{
|
|||
|
|
"firstName": "Juntao",
|
|||
|
|
"lastName": "Yu",
|
|||
|
|
"creatorType": "author"
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"firstName": "Alexandra",
|
|||
|
|
"lastName": "Uma",
|
|||
|
|
"creatorType": "author"
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"firstName": "Massimo",
|
|||
|
|
"lastName": "Poesio",
|
|||
|
|
"creatorType": "author"
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"date": "2020-05",
|
|||
|
|
"ISBN": "9791095546344",
|
|||
|
|
"abstractNote": "Anaphora resolution (coreference) systems designed for the CONLL 2012 dataset typically cannot handle key aspects of the full anaphora resolution task such as the identification of singletons and of certain types of non-referring expressions (e.g., expletives), as these aspects are not annotated in that corpus. However, the recently released dataset for the CRAC 2018 Shared Task can now be used for that purpose. In this paper, we introduce an architecture to simultaneously identify non-referring expressions (including expletives, predicative s, and other types) and build coreference chains, including singletons. Our cluster-ranking system uses an attention mechanism to determine the relative importance of the mentions in the same cluster. Additional classifiers are used to identify singletons and non-referring markables. Our contributions are as follows. First all, we report the first result on the CRAC data using system mentions; our result is 5.8% better than the shared task baseline system, which used gold mentions. Second, we demonstrate that the availability of singleton clusters and non-referring expressions can lead to substantially improved performance on non-singleton clusters as well. Third, we show that despite our model not being designed specifically for the CONLL data, it achieves a score equivalent to that of the state-of-the-art system by Kantor and Globerson (2019) on that dataset.",
|
|||
|
|
"conferenceName": "LREC 2020",
|
|||
|
|
"language": "English",
|
|||
|
|
"libraryCatalog": "ACLWeb",
|
|||
|
|
"pages": "11–20",
|
|||
|
|
"place": "Marseille, France",
|
|||
|
|
"proceedingsTitle": "Proceedings of the 12th Language Resources and Evaluation Conference",
|
|||
|
|
"publisher": "European Language Resources Association",
|
|||
|
|
"url": "https://www.aclweb.org/anthology/2020.lrec-1.2",
|
|||
|
|
"attachments": [
|
|||
|
|
{
|
|||
|
|
"title": "Full Text PDF",
|
|||
|
|
"mimeType": "application/pdf"
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"tags": [],
|
|||
|
|
"notes": [],
|
|||
|
|
"seeAlso": []
|
|||
|
|
}
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"type": "web",
|
|||
|
|
"url": "https://www.aclanthology.org/volumes/2020.lrec-1/",
|
|||
|
|
"items": "multiple"
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"type": "web",
|
|||
|
|
"url": "https://www.aclanthology.org/T87-1010.bib",
|
|||
|
|
"items": [
|
|||
|
|
{
|
|||
|
|
"itemType": "conferencePaper",
|
|||
|
|
"title": "Unification and the new grammatism",
|
|||
|
|
"creators": [
|
|||
|
|
{
|
|||
|
|
"firstName": "Steve",
|
|||
|
|
"lastName": "Pulman",
|
|||
|
|
"creatorType": "author"
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"date": "1987",
|
|||
|
|
"conferenceName": "TINLAP 1987",
|
|||
|
|
"libraryCatalog": "ACLWeb",
|
|||
|
|
"proceedingsTitle": "Theoretical Issues in Natural Language Processing 3",
|
|||
|
|
"url": "https://www.aclweb.org/anthology/T87-1010",
|
|||
|
|
"attachments": [
|
|||
|
|
{
|
|||
|
|
"title": "Full Text PDF",
|
|||
|
|
"mimeType": "application/pdf"
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"tags": [],
|
|||
|
|
"notes": [],
|
|||
|
|
"seeAlso": []
|
|||
|
|
}
|
|||
|
|
]
|
|||
|
|
}
|
|||
|
|
]
|
|||
|
|
/** END TEST CASES **/
|