| Challenge: | Existing methods for judging temporal relations are limited to “salient” event pairs or on pairs in a fixed window of sentences. |
| Approach: | They propose a new method to obtain temporal relations from absolute time value (a.k.a. time anchors) they start from time anchor for events and time expressions and induced temporal relation annotations automatically . |
| Outcome: | The proposed method shows that it requires less annotation effort and induces inter-sentence relations easily. |
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TIMELINE: Exhaustive Annotation of Temporal Relations Supporting the Automatic Ordering of Events in News Articles (2023.emnlp-main)
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| Challenge: | Existing temporal relation extraction models have low inter-annotator agreement due to lack of specificity of annotation guidelines . authors propose a method for annotating all temporal relations, including long-distance ones, which automates the process . |
| Approach: | They propose a new annotation scheme that defines criteria for temporal relations to be annotated . scheme includes events even if they are not expressed as verbs, they argue . |
| Outcome: | The proposed method reduces time and manual effort on the part of annotators. |
Comprehensive Annotation of Various Types of Temporal Information on the Time Axis (L18-1)
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| Challenge: | Existing studies linking event and time information have been conducted to train and evaluate models. |
| Approach: | They propose an annotation scheme that anchors expressions in text to the time axis comprehensively. |
| Outcome: | The proposed scheme can be utilized for integrated information analysis of events, entities and time. |
Structured Interpretation of Temporal Relations (L18-1)
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| Challenge: | Temporal relations between events and time expressions are often modeled in an unstructured manner, resulting in inconsistent and incomplete annotation and computational modeling. |
| Approach: | They propose an annotation approach where events and time expressions form a dependency tree in which each dependency relation corresponds to an instance of temporal anaphora. |
| Outcome: | The proposed approach annotates 235 documents in news and narratives with 48 doubly annotated documents. |
Utilizing Relative Event Time to Enhance Event-Event Temporal Relation Extraction (2021.emnlp-main)
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| Challenge: | Existing methods for event-event temporal relation extraction are sparse on event-time information. |
| Approach: | They propose a model for event-event temporal relation classification and an auxiliary task, relative event time prediction, which predicts the event time as real numbers. |
| Outcome: | The proposed model significantly improves the RoBERTa-based baseline and achieves state-of-the-art performance on MATRES dataset. |
Temporal Relations Annotation and Extrapolation Based on Semi-intervals and Boundig Relations (2020.coling-main)
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| Challenge: | Existing methods for temporal relations annotation and management are not widely used because they are too complex from the computational perspective. |
| Approach: | They propose a system for the annotation and management of temporal relations that combines the richness and expressiveness of Freksa’s approach with the simplicity of Allen’s notation. |
| Outcome: | The proposed system achieves more agreeable representations of temporal relations without increasing the complexity of the labeling process. |
Temporal Information Extraction by Predicting Relative Time-lines (D18-1)
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| Challenge: | a new paradigm for temporal information extraction from text evades the relation extraction phase because there are n 2 possible entity pairs in a text with n temporal entities. |
| Approach: | They propose a method to construct a linear time-line from a set of temporal relations from text without the intermediate step of prediction of tempor relations. |
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Improving Temporal Relation Extraction with a Globally Acquired Statistical Resource (N18-1)
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| Challenge: | Existing temporal extraction systems that extract temporal relations can be improved by using a resource that provides prior knowledge of the temporal order that events usually follow. |
| Approach: | They propose to use a probabilistic knowledge base acquired in the news domain to extract temporal relations between events from the New York Times articles over a 20-year span. |
| Outcome: | The proposed system and resource are both publicly available. |
A Multi-Axis Annotation Scheme for Event Temporal Relations (P18-1)
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| Challenge: | Existing temporal relation (TempRel) annotation schemes have low inter-annotator agreements even between experts, suggesting that the current annotation task needs a better definition. |
| Approach: | They propose to annotate temporal relation (TempRel) annotation schemes based on event start-points instead of a conventional 60’s-80’s model. |
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Fine-Grained Temporal Relation Extraction (P19-1)
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| Challenge: | Existing methods for temporal relations and event durations are insufficient for determining the fine-grained temporal structure of complex events. |
| Approach: | They propose a semantic framework for temporal relations and event durations that maps pairs of events to real-valued scales. |
| Outcome: | The proposed framework can predict fine-grained temporal relations and event durations . it can be applied to the entire English Web Treebank dataset . |
An Improved Neural Baseline for Temporal Relation Extraction (D19-1)
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| Challenge: | Existing datasets are small and/or have low inter-annotator agreements. |
| Approach: | They propose a new neural system that achieves 10% absolute accuracy improvement over the previous best system. |
| Outcome: | The proposed system achieves 10% absolute improvement over the previous best system on two benchmark datasets. |