Triple

T3472223
Position Surface form Disambiguated ID Type / Status
Subject Tanimachi Line E73288 entity
Predicate locatedIn P40 FINISHED
Object Osaka E486 NE FINISHED

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: [Tanimachi Line, locatedIn, Osaka]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Osaka
Context triple: [Tanimachi Line, locatedIn, 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. Higashiōsaka
    Higashiōsaka is an industrial and residential city in Japan known for its manufacturing base and location within the Osaka metropolitan area.
  • D. Suita, Osaka
    Suita, Osaka is a city in northern Osaka Prefecture, Japan, known as a major suburban and educational hub that hosts the main campus of Osaka University.
  • E. Yokohama
    Yokohama is Japan’s second-largest city and a major international port located just south of Tokyo.
  • 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_69ad85b2fed48190948c8765e453d270 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adbb3cc8488190b97c732e3f600a90 completed March 8, 2026, 6:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4880c8d4c819083a0f49598dbb2d2 completed March 13, 2026, 9:56 p.m.
Created at: March 8, 2026, 3:17 p.m.