SOTAVerified

Temporal Relation Extraction

Temporal relation extraction systems aim to identify and classify the temporal relation between a pair of entities provided in a text. For instance, in the sentence "Bob sent a message to Alice while she was leaving her birthday party." one can infer that the actions "sent" and "leaving" entails a temporal relation that can be described as "simultaneous".

Papers

Showing 76–88 of 88 papers

TitleStatusHype
Structured Learning for Temporal Relation Extraction from Clinical RecordsCode0
Neural Temporal Relation Extraction—0
Temporal information extraction from clinical text—0
CATENA: CAusal and TEmporal relation extraction from NAtural language textsCode0
Global Inference to Chinese Temporal Relation Extraction—0
Improving Temporal Relation Extraction with Training Instance Augmentation—0
Extracting Temporal and Causal Relations between Events—0
Combining Temporal Information and Topic Modeling for Cross-Document Event Ordering—0
Annotating Inter-Sentence Temporal Relations in Clinical Notes—0
Towards Unsupervised Learning of Temporal Relations between Events—0
Spanish TimeBank 1.0—0
TempEval-3: Evaluating Events, Time Expressions, and Temporal RelationsCode0
SemEval-2010 Task 13: TempEval-2—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1GPT-4o (CoT)Text Score59.2—Unverified
2GPT-4oText Score54—Unverified
3Qwen2-VL-72BText Score50.4—Unverified
4LLaVA-OneVision-Qwen2-72BText Score48.4—Unverified
5LLaVA-OneVision-Qwen2-7BText Score41.6—Unverified
6Qwen2-VL-7BText Score40.2—Unverified
7Gemini-1.5-Pro (CoT)Text Score37—Unverified
8VideoLLaMA2-72BText Score36.2—Unverified
9Gemini-1.5-ProText Score35.8—Unverified
10Claude 3.5 SonnetText Score32.8—Unverified