Triple

T7497234
Position Surface form Disambiguated ID Type / Status
Subject Tokyu railway network E177162 entity
Predicate serves P98 FINISHED
Object Ota, Tokyo E282024 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: Ota, Tokyo | Statement: [Tokyu railway network, serves, Ota, Tokyo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ota, Tokyo
Context triple: [Tokyu railway network, serves, Ota, Tokyo]
  • A. Ōta, Tokyo chosen
    Ōta, Tokyo is a large ward in southern Tokyo known for its mix of residential and industrial areas and for hosting Haneda Airport, one of Japan’s major international gateways.
  • B. Tōkyō-wan
    Tōkyō-wan is the Japanese name for Tokyo Bay, a major urban bay on the Pacific coast of Honshu that serves as a key economic and transportation hub for the Greater Tokyo Area.
  • C. Chuo City, Tokyo
    Chuo City, Tokyo is a central ward of Tokyo known for its historic commercial districts like Nihonbashi and Ginza, serving as a major hub for finance, retail, and culture.
  • D. Aoyama, Tokyo
    Aoyama, Tokyo is an upscale neighborhood in Minato Ward known for its fashionable boutiques, trendy cafes, art galleries, and modern architecture.
  • E. Yokohama
    Yokohama is Japan’s second-largest city and a major international port located just south of Tokyo.
  • 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_69c69f2583808190bd1a4936c42a5815 completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f5963d98819098275b161848d2d4 completed March 27, 2026, 9:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69c89a7aada08190b241c078871dc864 completed March 29, 2026, 3:20 a.m.
Created at: March 27, 2026, 3:44 p.m.