Triple

T2579928
Position Surface form Disambiguated ID Type / Status
Subject Tama Cemetery E57064 entity
Predicate locatedIn P40 FINISHED
Object Kokubunji, Tokyo E244087 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: Kokubunji, Tokyo | Statement: [Tama Cemetery, locatedIn, Kokubunji, Tokyo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kokubunji, Tokyo
Context triple: [Tama Cemetery, locatedIn, Kokubunji, Tokyo]
  • A. Bunkyo, Tokyo
    Bunkyo, Tokyo is a central special ward of Tokyo known for its educational institutions, cultural sites, and major sports venues such as the Tokyo Dome.
  • B. Asakusa
    Asakusa is a historic district in Tokyo best known for its ancient Sensō-ji Temple, traditional shopping streets, and preserved old-town atmosphere.
  • C. Kokubunji chosen
    Kokubunji is a city in western Tokyo, Japan, known as a residential and educational hub within the Tama area.
  • D. Ueno
    Ueno is a major district in Tokyo known for Ueno Park, its museums, zoo, and busy transportation hub.
  • E. Toshima, Tokyo
    Toshima, Tokyo is a special ward in northwestern Tokyo known for its major commercial and entertainment hub Ikebukuro and its mix of residential, educational, and cultural institutions.
  • 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_69ab4a4dca6481908c301f8e317396e7 completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abd3a9fd3c8190a521931e40cd801c completed March 7, 2026, 7:28 a.m.
NED1 Entity disambiguation (via context triple) batch_69af6579bab88190891c23721eaccfc8 completed March 10, 2026, 12:27 a.m.
Created at: March 6, 2026, 9:49 p.m.