Papers by Hiroki Teranishi
Arukikata Travelogue Dataset with Geographic Entity Mention, Coreference, and Link Annotation (2024.findings-eacl)
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Shohei Higashiyama, Hiroki Ouchi, Hiroki Teranishi, Hiroyuki Otomo, Yusuke Ide, Aitaro Yamamoto, Hiroyuki Shindo, Yuki Matsuda, Shoko Wakamiya, Naoya Inoue, Ikuya Yamada, Taro Watanabe
| Challenge: | et al., 2006) considers geographic relatedness among geo-entity mentions in document-level geoparsing. |
| Approach: | They present a Japanese travelogue dataset that considers geographic relatedness among geo-entity mentions. |
| Outcome: | The proposed dataset includes 200 travelogue documents with rich geo-entity information . it shows that human activities, mobility, and events are often described with natural language expressions of locations or geographic entities (geo-entities) |
Coordination Generation via Synchronized Text-Infilling (2022.coling-1)
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| Challenge: | Generating synthetic data from pre-trained language models has enhanced performance across several NLP tasks. |
| Approach: | They propose a method for generating sentences with a coordinate structure in which the boundaries of its conjuncts are explicitly specified. |
| Outcome: | The proposed method produces promising coordination instances that provide gains for the task in low-resource settings. |
A Text Embedding Model with Contrastive Example Mining for Point-of-Interest Geocoding (2025.coling-main)
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| Challenge: | Existing studies have focused on coarse-grained locations, but we focus on fine-grain POIs, which have many candidates with similar names. |
| Approach: | They develop a text embedding-based geocoding model and investigate (1) entry encoding representations and (2) hard negative mining approaches suitable for enhancing the model’s disambiguation ability. |
| Outcome: | The proposed model significantly improves its disambiguation ability and entry encoding representations. |
Decomposed Local Models for Coordinate Structure Parsing (N19-1)
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| Challenge: | Existing methods for coordination boundary identification are inefficient, even for humans. |
| Approach: | They propose a simple and accurate model for coordination boundary identification . they combine syntactic parsers and neural networks to compute similarity and replaceability features of conjuncts . |
| Outcome: | The proposed model outperforms similarity-based approaches but cannot handle more than two conjuncts in a coordination and multiple coordinations at once. |
PolyNERE: A Novel Ontology and Corpus for Named Entity Recognition and Relation Extraction in Polymer Science Domain (2024.lrec-main)
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| Challenge: | a new ontology for polymer-relevant entities and relations is available for training data . the ontologies are customizable to adapt to specific research needs. |
| Approach: | They propose a polymer-relevant ontology featuring crucial entities and relations . the ontologies are customizable to adapt to specific research needs . |
| Outcome: | The proposed ontology can extract polymer-relevant information from scientific papers . it can be customized to adapt to specific research needs . |
Graph-Structured Trajectory Extraction from Travelogues (2025.acl-long)
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Aitaro Yamamoto, Hiroyuki Otomo, Hiroki Ouchi, Shohei Higashiyama, Hiroki Teranishi, Hiroyuki Shindo, Taro Watanabe
| Challenge: | Existing studies treat travelogues as sequences of visited locations, but they lack a benchmark dataset. |
| Approach: | They propose to represent the trajectory as a graph that can capture the hierarchy as well as the visiting order and construct a benchmark dataset for the extraction. |
| Outcome: | The proposed dataset shows that even naive baseline systems can predict visited locations and the visiting order between them, while it is more challenging to predict the hierarchical relations. |
JaCorpTrack: Corporate History Event Extraction for Tracking Organizational Changes (2025.emnlp-industry)
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Yuya Sawada, Hiroki Ouchi, Yuichiro Yasui, Hiroki Teranishi, Yuji Matsumoto, Taro Watanabe, Masayuki Ishii
| Challenge: | Existing information extraction systems are not able to accurately capture organizational changes. |
| Approach: | They propose a task to extract corporate history events related to organizational changes by identifying company names before and after each event, as well as the corresponding date. |
| Outcome: | The proposed task is designed to identify company names before and after an event, as well as the corresponding date. |
Coordination Boundary Identification without Labeled Data for Compound Terms Disambiguation (2020.coling-main)
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Yuya Sawada, Takashi Wada, Takayoshi Shibahara, Hiroki Teranishi, Shuhei Kondo, Hiroyuki Shindo, Taro Watanabe, Yuji Matsumoto
| Challenge: | a new method for nominal coordination boundary identification is proposed . it uses pre-trained word embeddings to measure similarities of words and detects the span of coordination . |
| Approach: | They propose a method for nominal coordination boundary identification that uses pre-trained word embeddings to measure similarities of words and detects the span of coordination. |
| Outcome: | The proposed method can identify coordination boundaries without training on labeled data . it is comparable to a recent supervised method for the case when the coordinator conjoins simple noun phrases. |