SOTAVerified

Temporal Information Extraction

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.







 PRI20001020.2000.0127 
 NEWS STORY 
 10/20/2000 20:02:07.85 


 The Navy has changed its account of the attack on the USS Cole in Yemen.
 Officials now say the ship was hit nearly two hours 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.


 10/20/2000 20:02:28.05 






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

Papers

Showing 1–25 of 86 papers

TitleStatusHype
SoftTiger: A Clinical Foundation Model for Healthcare WorkflowsCode7
Rethinking Efficient and Effective Point-based Networks for Event Camera Classification and Regression: EventMambaCode2
Ontology-driven weak supervision for clinical entity classification in electronic health recordsCode1
Think Step by Step: Chain-of-Gesture Prompting for Error Detection in Robotic Surgical VideosCode1
Make-An-Audio 2: Temporal-Enhanced Text-to-Audio GenerationCode1
tieval: An Evaluation Framework for Temporal Information Extraction SystemsCode1
BCCWJ-TimeBank: Temporal and Event Information Annotation on Japanese Text—0
Annotating Inter-Sentence Temporal Relations in Clinical Notes—0
Fusing Temporal Graphs into Transformers for Time-Sensitive Question Answering—0
Brundlefly at SemEval-2016 Task 12: Recurrent Neural Networks vs. Joint Inference for Clinical Temporal Information Extraction—0
Automatic Extraction of Time Expressions Accross Domains in French Narratives—0
CDE-IIITH at SemEval-2016 Task 12: Extraction of Temporal Information from Clinical documents using Machine Learning techniques—0
CENTAL at SemEval-2016 Task 12: a linguistically fed CRF model for medical and temporal information extraction—0
Chinese Temporal Tagging with HeidelTime—0
A Survey on Temporal Reasoning for Temporal Information Extraction from Text (Extended Abstract)—0
Extracting Narrative Timelines as Temporal Dependency Structures—0
Context-Aware Neural Model for Temporal Information Extraction—0
ClearTK-TimeML: A minimalist approach to TempEval 2013—0
Brundlefly at SemEval-2016 Task 12: Recurrent Neural Networks vs. Joint Inference for Clinical Temporal Information Extraction—0
Dense Event Ordering with a Multi-Pass Architecture—0
Document Level Time-anchoring for TimeLine Extraction—0
Empirical Validation of Reichenbach's Tense Framework—0
Extending HeidelTime for Temporal Expressions Referring to Historic Dates—0
Extracting Events with Informal Temporal References in Personal Histories in Online Communities—0
BluLab: Temporal Information Extraction for the 2015 Clinical TempEval Challenge—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Ning et al.Temporal awareness67.2—Unverified
2ClearTKTemporal awareness30.98—Unverified
#ModelMetricClaimedVerifiedStatus
1CatenaF1 score0.51—Unverified
2CAEVOF1 score0.51—Unverified