Hirotaka Kameko — accepted AI-conference papers

2024

Automatic Construction of a Large-Scale Corpus for Geoparsing Using Wikipedia Hyperlinks

Keyaki Ohno, Hirotaka Kameko, Keisuke Shirai, Taichi Nishimura, Shinsuke Mori

COLING 2024main

Geoparsing is the task of estimating the latitude and longitude (coordinates) of location expressions in texts. Geoparsing must deal with the ambiguity of the expressions that indicate multiple locations with the same notation. For evaluating geoparsing systems, several corpora have been proposed in…

Cited by 0 Source ↗PDF ↗Scholar ↗

2022

Visual Recipe Flow: A Dataset for Learning Visual State Changes of Objects with Recipe Flows

Keisuke Shirai, Atsushi Hashimoto, Taichi Nishimura, Hirotaka Kameko, Shuhei Kurita, Yoshitaka Ushiku +1

COLING 2022main

We present a new multimodal dataset called Visual Recipe Flow, which enables us to learn a cooking action result for each object in a recipe text. The dataset consists of object state changes and the workflow of the recipe text. The state change is represented as an image pair, while the workflow is…

Cited by 11 Source ↗PDF ↗Scholar ↗