Triple

T262036
Position Surface form Disambiguated ID Type / Status
Subject Tokyo E5560 entity
Predicate contains P35 FINISHED
Object Ueno E72187 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: Ueno | Statement: [Tokyo, contains, Ueno]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ueno
Context triple: [Tokyo, contains, Ueno]
  • A. Toyonaka
    Toyonaka is a suburban city in Japan’s Kansai region known for its residential neighborhoods, educational institutions, and proximity to central Osaka.
  • B. Asakusa chosen
    Asakusa is a historic district in Tokyo best known for its ancient Sensō-ji Temple, traditional shopping streets, and preserved old-town atmosphere.
  • C. Chiyoda
    Chiyoda is a central special ward of Tokyo that serves as Japan’s political and administrative hub, housing the Imperial Palace, the National Diet, and many government institutions.
  • D. Moriguchi
    Moriguchi is a city in Japan’s Kansai region that forms part of the Osaka metropolitan area and serves as a residential and commercial hub.
  • E. Minoh
    Minoh is a suburban city in northern Osaka Prefecture, Japan, known for its scenic Minoh Waterfall, autumn foliage, and residential communities.
  • 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_69a2580a64ac8190ad76e34bb0715b5e completed Feb. 28, 2026, 2:50 a.m.
NER Named-entity recognition batch_69a25d7428dc8190ae12b12a21fcc6cb completed Feb. 28, 2026, 3:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69a50e1f11c08190a0fb6198ca7b61e8 completed March 2, 2026, 4:12 a.m.
Created at: Feb. 28, 2026, 2:55 a.m.