Triple

T15888882
Position Surface form Disambiguated ID Type / Status
Subject Wing Building store section E385263 entity
Predicate locatedInCity P40 FINISHED
Object Osaka NE ONNED1

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Osaka | Statement: [Wing Building store section, locatedInCity, Osaka]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Osaka
Context triple: [Wing Building store section, locatedInCity, Osaka]
  • A. Osaka chosen
    Osaka is Japan's third-largest city and a major economic, cultural, and historical hub known for its vibrant street food, bustling nightlife, and role as a commercial center in the Kansai region.
  • B. Nagoya
    Nagoya is a major industrial and commercial city in central Japan, known as a manufacturing hub and the capital of Aichi Prefecture.
  • C. Settsu, Osaka
    Settsu, Osaka is a suburban city in northern Osaka Prefecture, Japan, known for its residential neighborhoods and convenient access to the Osaka metropolitan area.
  • D. Higashiōsaka
    Higashiōsaka is an industrial and residential city in Japan known for its manufacturing base and location within the Osaka metropolitan area.
  • E. Nankoku City
    Nankoku City is a regional city on the island of Shikoku in Japan, known for its agricultural production and proximity to the city of Kōchi.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d86da5b800819083a31be937d738b0 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1561c3d008190a892f091a2f874cf completed April 16, 2026, 9:35 p.m.
NED1 Entity disambiguation (via context triple) batch_6a01953eaa6c819091f7d63a1e3e7070 in_progress May 11, 2026, 8:37 a.m.
Created at: April 10, 2026, 4:51 a.m.