Showing posts with label entity discovery and linking. Show all posts
Showing posts with label entity discovery and linking. Show all posts

Friday, May 15, 2020

LDC 2020 May Newsletter

New Publications:
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New publications: 

(1) LORELEI Oromo Incident Language Pack was developed by LDC and is comprised of approximately 3.9 million words of Oromo monolingual text, 25,000 words of English monolingual text, 135,000 words of parallel and comparable Oromo-English text, and 50,000 words of data annotated for Entity Discovery and Linking and Situation Frames. It contains all of the text data, annotations, supplemental resources and related software tools for the Oromo language that were used in the DARPA LORELEI / LoReHLT 2017 Evaluation. 

The evaluation protocol was based on a scenario in which an unforeseen event triggered a need for humanitarian and logistical support in a region where the incident language had received little or no attention in NLP research. Evaluation participants provided NLP solutions, including information extraction and machine translation, with limited resources and limited development time.

Data was collected from news, social network, weblog, newsgroup, discussion forum, and reference material. Entity Detection and Linking and Situation Frame annotations identified “entities,” “needs” (such as a need for food) and “issues” (such as civil unrest) to be detected by systems for scoring purposes. Situation frame analysis was designed to extract basic information that would be useful for planning a disaster response effort. 

The knowledge base for the entity linking annotation in this corpus is available separately as LORELEI Entity Detection and Linking Knowledge Base (LDC2020T10).

LORELEI Oromo Incident Language Pack is distributed via web download.

2020 Subscription Members will automatically receive copies of this corpus. 2020 Standard Members may request a copy as part of their 16 free membership corpora. Non-members may license this data for a fee.

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(1) LORELEI Entity Detection and Linking Knowledge Base was developed by LDC and contains the full LORELEI Entity Detection and Linking (EDL) Knowledge Base (KB) used for all LORELEI Representative Language and Incident Language Pack entity linking annotation. The LORELEI (Low Resource Languages for Emergent Incidents) Program was concerned with building human language technology for low resource languages in the context of emergent situations like natural disasters or disease outbreaks. 

The KB in this release supported the EDL task in LORELEI for four entity types -- geo-political entities (GPE), locations (LOC), persons (PER) and organizations (ORG) -- and contains a total of 10,216,832 entities. There are four inputs to the KB, each designated by a unique "origin" code in the KB, as follows: GPE and LOC entities from a snapshot of GeoNames, PER entities from the CIA World Leaders List, ORG entities from Appendix B of the CIA World Factbook, and additional entities manually created by LDC for each of the representative and incident languages in the LORELEI Program. 

LORELEI Entity Detection and Linking Knowledge Base is distributed via web download.

2020 Subscription Members will automatically receive copies of this corpus. 2020 Standard Members may request a copy as part of their 16 free membership corpora. Non-members may license this data for a fee.

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(3) BOLT English Translation Treebank - Chinese Discussion Forum was developed by LDC and consists of 147,432 tokens of web discussion forum data translated from Chinese to English and annotated for part-of-speech and syntactic structure. 

The source data is Chinese discussion forum web text collected by LDC in 2011 and 2012, translated into English and released in BOLT Chinese Discussion Forum Parallel Training Data (LDC2017T05). A subset of the translated text -- 148 files representing 147,432 tokens -- was selected for the treebank and annotated for word-level tokenization, part-of-speech and syntactic structure. Only the translated English text is included in the source data for this release. 

Part-of-speech and treebank annotation conformed to Penn Treebank II style, incorporating changes to those guidelines that were developed under the GALE (Global Autonomous Language Exploitation) program. Supplementary guidelines for English treebanks and web text are included with this release.

BOLT English Translation Treebank - Chinese Discussion Forum is distributed via web download.

2020 Subscription Members will automatically receive copies of this corpus. 2020 Standard Members may request a copy as part of their 16 free membership corpora. Non-members may license this data for a fee.

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(4) Multi-Language Conversational Telephone Speech 2011 -- Mandarin Chinese was developed by LDC and is comprised of approximately 25 hours of telephone speech in Mandarin Chinese.

The data were collected primarily to support research and technology evaluation in automatic language identification, and portions of these telephone calls were used in the NIST 2011 Language Recognition Evaluation (LRE). Participants were recruited by native speakers who contacted acquaintances in their social network. Those native speakers made one call, up to 15 minutes, to each acquaintance. The data was collected using LDC's telephone collection infrastructure, comprised of three computer telephony systems. Human auditors labeled calls for callee gender, dialect type and noise. 

LDC has also released the following as part of the Multi-Language Conversational Telephone Speech 2011 series:
Multi-Language Conversational Telephone Speech 2011 -- Mandarin Chinese is distributed via web download. 

2020 Subscription Members will automatically receive copies of this corpus. 2020 Standard Members may request a copy as part of their 16 free membership corpora. Non-members may license this data for a fee. 

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Friday, December 6, 2019

LDC 2019 December Newsletter


LDC Membership Discounts for MY2020 Still Available
Spring 2020 Data Scholarship Program – deadline approaching 
Introducing LanguageArc: A Citizen Linguist Portal 

New Publications: 
MagicData Chinese Mandarin Conversational Speech 
BOLT Egyptian Arabic-EnglishWord Alignment -- SMS/Chat Training 
TAC KBP Entity Discovery and Linking - Comprehensive Evaluation Data 2016-2017 
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LDC Membership Discounts for MY2020 Still Available 

Join LDC while membership savings are still available. Now through March 2, 2020, current MY2019 members who renew their LDC membership receive a 10% discount off the membership fee. New or returning member organizations receive a 5% discount through March 2. Membership remains the most economical way to access LDC releases. Visit Join LDC for details on membership options and benefits. 

Spring 2020 Data Scholarship Program – deadline approaching 

Students can apply for the Spring 2020 Data Scholarship Program now through January 15, 2020. The LDC Data Scholarship program provides students with no-cost access to LDC data. For more information on application requirements and program rules, please visit LDC Data Scholarships.

Introducing LanguageArc: A Citizen Linguist Portal 

LanguageARC is a citizen science website for languages developed with a grant from the National Science Foundation (no. 170377). Contributors to this online community – “citizen linguists” – participate in a variety of tasks and activities that support linguistic research, such as identifying accents from audio clips, recording “tongue twisters,” and translating English sentences into other languages. Data collected from LanguageArc will be made freely available to the research community. New collection and annotation projects will be added on an ongoing basis, and researchers will soon be able to create their own LanugageArc projects with an easy-to-use Project Builder Toolkit.  All are encouraged to explore the site and participate in the community. Comments, questions and suggestions are welcome via the site’s Contact page. 
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New publications:

(1) Magic Data Chinese Mandarin Conversational Speech was developed by Beijing Magic Data Technology Co., Ltd. and consists of approximately 10 hours of Mandarin conversational speech from 60 speakers. Each conversation was recorded on multiple devices and is presented in multiple forms, resulting in a total of approximately 60 hours of audio with corresponding transcripts.

All participants were native speakers of Mandarin in Mainland China from accent regions across the country. Speakers were paired for conversations on a range of topics, including travel, fitness, games, sports and pets. Metadata such as topic, collection date, mobile device and speaker demographic information is available in the documentation accompanying this release. 

Magic Data Chinese Mandarin Conversational Speech is distributed via web download.

2019 Subscription Members will automatically receive copies of this corpus. 2019 Standard Members may request a copy as part of their 16 free membership corpora. Non-members may license this data for a fee.

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(2) BOLT Egyptian Arabic-English Word Alignment -- SMS/Chat Training was developed by LDC and consists of 349,414 words of Egyptian Arabic and English parallel text enhanced with linguistic tags to indicate word relations.

This release contains Egyptian Arabic source text message and chat conversations collected using two methods: new collection via LDC's collection platform, and donation of SMS or chat archives from BOLT collection participants. The source data is released as BOLT Egyptian Arabic SMS/Chat and Transliteration (LDC2017T07).

The BOLT word alignment task was built on treebank annotation. Egyptian Arabic source tree tokens were automatically extracted from tree files in LDC’s BOLT Egyptian Arabic Treebank, which had been tagged for part-of-speech and syntactically annotated. That data was then aligned and annotated for the word alignment task. 

BOLT Egyptian Arabic-English Word Alignment -- SMS/Chat Training is distributed via web download.

2019 Subscription Members will automatically receive copies of this corpus. 2019 Standard Members may request a copy as part of their 16 free membership corpora. Non-members may license this data for a fee. 

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(3) TAC KBP Entity Discovery and Linking - Comprehensive Evaluation Data 2016-2017 was developed by LDC and contains training and evaluation data produced in support of the TAC KBP Entity Discovery and Linking (EDL) tasks in 2016 and 2017. This corpus includes queries, knowledge base (KB) links, equivalence class clusters for NIL entities, and entity type information for each of the queries. The EDL reference KB, to which EDL data are linked, is available separately in TAC KBP Entity Discovery and Linking - Comprehensive Training and Evaluation Data 2014-2015 (LDC2019T02). 

The goal of the EDL track is to conduct end-to-end entity extraction, linking and clustering. For producing gold standard data, given a document collection, annotators (1) extract (identify and classify) entity mentions (queries), link them to nodes in a reference KB and (2) perform cross-document co-reference on within-document entity clusters that cannot be linked to the KB.

Source data for the annotations consists of Chinese, English and Spanish newswire and discussion forum text collected by LDC and is available in TAC KBP Evaluation Source Corpora 2016-2017 (LDC2019T12).

TAC KBP Entity Discovery and Linking - Comprehensive Evaluation Data 2016-2017 is distributed via web download.


2019 Subscription Members will automatically receive copies of this corpus. 2019 Standard Members may request a copy as part of their 16 free membership corpora. Non-members may license this data for a fee.