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

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Showing 26–50 of 88 papers

TitleStatusHype
Global Inference to Chinese Temporal Relation Extraction—0
Improving Temporal Relation Extraction with Training Instance Augmentation—0
Improving Temporal Relation Extraction with a Globally Acquired Statistical Resource—0
Investigating the Challenges of Temporal Relation Extraction from Clinical Text—0
Is artificial data useful for biomedical Natural Language Processing algorithms?—0
Joint Constrained Learning for Event-Event Relation Extraction—0
Joint Event and Temporal Relation Extraction with Shared Representations and Structured Prediction—0
LIMSI-COT at SemEval-2017 Task 12: Neural Architecture for Temporal Information Extraction from Clinical Narratives—0
Zero-shot Temporal Relation Extraction with ChatGPT—0
A BERT-based One-Pass Multi-Task Model for Clinical Temporal Relation Extraction—0
A BERT-based Universal Model for Both Within- and Cross-sentence Clinical Temporal Relation Extraction—0
An Improved Neural Baseline for Temporal Relation Extraction—0
Annotating Inter-Sentence Temporal Relations in Clinical Notes—0
A Structured Learning Approach to Temporal Relation Extraction—0
Attention Neural Model for Temporal Relation Extraction—0
Beyond Pairwise: Global Zero-shot Temporal Graph Generation—0
Combining Temporal Information and Topic Modeling for Cross-Document Event Ordering—0
Context-Dependent Semantic Parsing for Temporal Relation Extraction—0
Contextualized Word Embeddings Enhanced Event Temporal Relation Extraction for Story Understanding—0
Cross-Document Temporal Relation Extraction with Temporal Anchoring Events—0
DCT-Centered Temporal Relation Extraction—0
Distinguishing Between Foreground and Background Events in News—0
Ensemble-based Fine-Tuning Strategy for Temporal Relation Extraction from the Clinical Narrative—0
EntityBERT: Entity-centric Masking Strategy for Model Pretraining for the Clinical Domain—0
Event Temporal Relation Extraction based on Retrieval-Augmented on LLMs—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