Triple

T6638779
Position Surface form Disambiguated ID Type / Status
Subject Hokusetsu Mountains E150526 entity
Predicate accessFrom P1985 FINISHED
Object Toyonaka E24760 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: Toyonaka | Statement: [Hokusetsu Mountains, accessFrom, Toyonaka]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Toyonaka
Context triple: [Hokusetsu Mountains, accessFrom, 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. Nishi-Tobecho
    Nishi-Tobecho is a notable neighborhood within Nishi Ward in Yokohama, Japan, known as part of the city’s central urban area.
  • C. Kagurazaka
    Kagurazaka is a historic neighborhood in central Tokyo known for its narrow cobblestone streets, traditional ryotei restaurants, and blend of old geisha district charm with modern boutiques and cafes.
  • D. Toshima
    Toshima is a special ward in northwest Tokyo known for the major commercial and entertainment hub of Ikebukuro and its dense urban residential districts.
  • E. Hamamatsuchō
    Hamamatsuchō is a business and transportation district in Tokyo known for its major train and monorail stations, office towers, and proximity to Tokyo Bay.
  • 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_69c687f0ceb08190bf40807bfc605fa5 completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6aff082b0819089f5a69aa67d5346 completed March 27, 2026, 4:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7cbabb8848190bb541957176b0ca1 completed March 28, 2026, 12:38 p.m.
Created at: March 27, 2026, 2 p.m.