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 41–50 of 88 papers

TitleStatusHype
0/1 Deep Neural Networks via Block Coordinate Descent—0
Temporal Relation Extraction with a Graph-Based Deep Biaffine Attention Model—0
Context-Dependent Semantic Parsing for Temporal Relation Extraction—0
Cross-Document Temporal Relation Extraction with Temporal Anchoring Events—0
Fine-grained Temporal Relation Extraction with Ordered-Neuron LSTM and Graph Convolutional Networks—0
VideoCLIP: Contrastive Pre-training for Zero-shot Video-Text UnderstandingCode0
TIMERS: Document-level Temporal Relation Extraction—0
Open Temporal Relation Extraction for Question Answering—0
EntityBERT: Entity-centric Masking Strategy for Model Pretraining for the Clinical Domain—0
Extracting Temporal Event Relation with Syntax-guided Graph TransformerCode0
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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