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Temporal Information Extraction

16 평가 기록 10 datasets

Temporal information extraction is the identification of chunks/tokens corresponding to temporal intervals, and the extraction and determination of the temporal relations between those. The entities extracted may be temporal expressions (timexes), eventualities (events), or auxiliary signals that support the interpretation of an entity or relation. Relations may be temporal links (tlinks), describing the order of events and times, or subordinate links (slinks) describing modality and other subordinative activity, or aspectual links (alinks) around the various influences aspectuality has on event structure.

The markup scheme used for temporal information extraction is well-described in the ISO-TimeML standard, and also on www.timeml.org.

<?xml version="1.0" ?>

<TimeML xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:noNamespaceSchemaLocation="http://timeml.org/timeMLdocs/TimeML_1.2.1.xsd">
<TEXT>


 PRI20001020.2000.0127 
 NEWS STORY 
 <TIMEX3 tid="t0" type="TIME" value="2000-10-20T20:02:07.85">10/20/2000 20:02:07.85</TIMEX3> 


 The Navy has changed its account of the attack on the USS Cole in Yemen.
 Officials <TIMEX3 tid="t1" type="DATE" value="PRESENT_REF" temporalFunction="true" anchorTimeID="t0">now</TIMEX3> say the ship was hit <TIMEX3 tid="t2" type="DURATION" value="PT2H">nearly two hours </TIMEX3>after it had docked.
 Initially the Navy said the explosion occurred while several boats were helping
 the ship to tie up. The change raises new questions about how the attackers
 were able to get past the Navy security.


 <TIMEX3 tid="t3" type="TIME" value="2000-10-20T20:02:28.05">10/20/2000 20:02:28.05</TIMEX3> 



<TLINK timeID="t2" relatedToTime="t0" relType="BEFORE"/>
</TEXT>
</TimeML>

To avoid leaking knowledge about temporal structure, train, dev and test splits must be made at document level for temporal information extraction.

개요는 각 항목의 일부입니다. 위 탭에서 전체 기록을 페이지별로 탐색할 수 있습니다.

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Dataset기록된 모델 예시MetricPaperCode
R2R
Strict Detection (Pr.): 96.37 Strict Detection (Re.): 96.37Strict Detection (F1): 96.37Relaxed Detection (Pr.): 100
논문 코드
Ning et al.
Temporal awareness: 67.2
논문 -
Catena
F1 score: 0.511
논문 코드
Lange et al.
F1: 47.87
논문 -
Lange et al.
F1: 64.21
논문 -
Lange et al.
F1: 62.58
논문 -
Hengam
Entity F1 (partial): 91.6
논문 코드
Lange et al.
F1: 66.53
논문 -
Lange et al.
F1: 79.55
논문 -
Lange et al.
F1: 75.47
논문 -

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