Triple

T12215853
Position Surface form Disambiguated ID Type / Status
Subject Yamaboko Junko E291081 entity
Predicate associatedWith P37 FINISHED
Object Gion district E83963 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: Gion district | Statement: [Yamaboko Junko, associatedWith, Gion district]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gion district
Context triple: [Yamaboko Junko, associatedWith, Gion district]
  • A. Gion district chosen
    Gion district is Kyoto’s famous traditional entertainment quarter, renowned for its historic wooden machiya houses, teahouses, and geisha (geiko and maiko) culture.
  • B. Koishikawa district
    Koishikawa district is a residential and educational neighborhood in Tokyo known for sites like Koishikawa Kōrakuen Garden and the University of Tokyo facilities.
  • C. Kawaramachi area
    The Kawaramachi area is a bustling commercial and entertainment district in central Kyoto known for its shopping streets, restaurants, and proximity to traditional nightlife alleys like Pontocho.
  • D. Kamitabashi
    Kamitabashi is a residential neighborhood located in the Kita ward of Tokyo, Japan.
  • E. Asakusa district
    Asakusa district is a historic neighborhood in Tokyo best known for its ancient Sensō-ji Temple, traditional shopping streets, and preserved old-town 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_69d6ab65923081909acfc61b7a612233 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d91c9419d48190b0037fe8edc681c4 completed April 10, 2026, 3:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6eac128408190a29b4f8a6e1240dd completed May 3, 2026, 6:27 a.m.
Created at: April 8, 2026, 9:51 p.m.