Triple

T15446457
Position Surface form Disambiguated ID Type / Status
Subject Hatanodai E370034 entity
Predicate locatedInAdministrativeTerritorialEntity P40 FINISHED
Object Shinagawa City NE NERFINISHED

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: Shinagawa City | Statement: [Hatanodai, locatedInAdministrativeTerritorialEntity, Shinagawa City]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Shinagawa City
Context triple: [Hatanodai, locatedInAdministrativeTerritorialEntity, Shinagawa City]
  • A. Shinagawa City chosen
    Shinagawa City is a special ward in Tokyo, Japan, known as a major commercial and transportation hub with a mix of business districts and residential neighborhoods.
  • B. Shibuya City
    Shibuya City is a major commercial and entertainment district in central Tokyo, Japan, famous for its bustling scramble crossing, youth culture, and fashion scene.
  • C. Bunkyō City
    Bunkyō City is a special ward in central Tokyo, Japan, known for its universities, historic temples, and quiet residential neighborhoods.
  • D. Sumida City
    Sumida City is a special ward of Tokyo, Japan, known for landmarks such as the Tokyo Skytree and its traditional downtown neighborhoods.
  • E. Kōtō City
    Kōtō City is a special ward in eastern Tokyo known for its waterfront areas, modern residential and commercial districts, and cultural sites such as museums and event venues.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d85a19180081909925012fbf4e62a3 completed April 10, 2026, 2:02 a.m.
NER Named-entity recognition batch_69e03ef767b4819099f2c0919a158321 completed April 16, 2026, 1:44 a.m.
Created at: April 10, 2026, 3:21 a.m.