Triple

T1127856
Position Surface form Disambiguated ID Type / Status
Subject Toyonaka E24760 entity
Predicate neighboringCity P988 FINISHED
Object Suita E26300 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: Suita | Statement: [Toyonaka, neighboringCity, Suita]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Suita
Context triple: [Toyonaka, neighboringCity, Suita]
  • A. Suita chosen
    Suita is a city in northern Osaka Prefecture, Japan, known as a residential and commercial hub that hosted part of Expo '70 and is home to Osaka University’s main campus.
  • B. Minoh
    Minoh is a suburban city in northern Osaka Prefecture, Japan, known for its scenic Minoh Waterfall, autumn foliage, and residential communities.
  • C. Moriguchi
    Moriguchi is a city in Japan’s Kansai region that forms part of the Osaka metropolitan area and serves as a residential and commercial hub.
  • D. Takarazuka
    Takarazuka is a Japanese city in Hyōgo Prefecture best known for the all-female Takarazuka Revue theater troupe and its popular hot spring resorts.
  • E. Daikanyama
    Daikanyama is a trendy, upscale neighborhood in Tokyo known for its stylish boutiques, cafes, and relaxed, residential atmosphere.
  • 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_69a4940712c88190aa244f3fc6070a65 completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bbdd39b88190bf46de38818fe2df completed March 1, 2026, 10:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69adeab2f888819093d2b3e49b105802 completed March 8, 2026, 9:31 p.m.
Created at: March 1, 2026, 7:44 p.m.