Triple

T17707136
Position Surface form Disambiguated ID Type / Status
Subject Department of Physics, Osaka University E441459 entity
Predicate city P40 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: [Department of Physics, Osaka University, city, Toyonaka]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Toyonaka
Context triple: [Department of Physics, Osaka University, city, 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. Yodoyabashi
    Yodoyabashi is a major business and commercial district in central Osaka, known for its financial institutions, offices, and convenient subway and rail connections.
  • C. Kamitabashi
    Kamitabashi is a residential neighborhood located in the Kita ward of Tokyo, Japan.
  • D. Asagaya
    Asagaya is a residential and commercial neighborhood in Tokyo known for its traditional shopping streets, local festivals, and convenient access to central Tokyo.
  • E. Komagome
    Komagome is a residential and commercial neighborhood in Tokyo known for its traditional atmosphere, historic temples, and the renowned Rikugien Garden.
  • 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_69d8b9ea20b48190ace88bb46b01e6a9 completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e47297f7188190ba859d71e394bd4b completed April 19, 2026, 6:13 a.m.
Created at: April 10, 2026, 10:05 a.m.