Triple

T14189143
Position Surface form Disambiguated ID Type / Status
Subject Osaka Airport Station E351660 entity
Predicate servesCity P82 FINISHED
Object Toyonaka NE NERFINISHED

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: Toyonaka | Statement: [Osaka Airport Station, servesCity, Toyonaka]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Toyonaka
Context triple: [Osaka Airport Station, servesCity, Toyonaka]
  • A. Toyonaka chosen
    Toyonaka is a suburban city in Japan’s Kansai region known for its residential neighborhoods, educational institutions, and proximity to central Osaka.
  • B. Kamitabashi
    Kamitabashi is a residential neighborhood located in the Kita ward of Tokyo, Japan.
  • C. Asagaya
    Asagaya is a residential and commercial neighborhood in Tokyo known for its traditional shopping streets, local festivals, and convenient access to central Tokyo.
  • D. Komagome
    Komagome is a residential and commercial neighborhood in Tokyo known for its traditional atmosphere, historic temples, and the renowned Rikugien Garden.
  • E. Nagatacho
    Nagatacho is a central district in Tokyo, Japan, known as the political heart of the country and home to key government institutions such as the National Diet Building.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d827894ac0819097803e57f3227b23 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de61de509881908967ef5031f2a8d9 completed April 14, 2026, 3:48 p.m.
Created at: April 10, 2026, 1:03 a.m.