Triple

T2882393
Position Surface form Disambiguated ID Type / Status
Subject Nankai Main Line E59425 entity
Predicate hasStation P35 FINISHED
Object Sakai Station E494859 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: Sakai Station | Statement: [Nankai Main Line, hasStation, Sakai Station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sakai Station
Context triple: [Nankai Main Line, hasStation, Sakai Station]
  • A. Sakai Station chosen
    Sakai Station is a major railway station in Sakai, Osaka Prefecture, Japan, functioning as an important hub for commuter and regional rail services.
  • B. Shindaita Station
    Shindaita Station is a railway station in Tokyo, Japan, serving passengers on the Keio Inokashira Line.
  • C. Shijō Station
    Shijō Station is a major underground metro station on the Kyoto Municipal Subway network, serving as a key transit point in central Kyoto near the city’s main commercial district.
  • D. Oimachi Station
    Oimachi Station is a major railway hub in Tokyo’s Shinagawa ward, serving multiple train and subway lines and connecting local neighborhoods with central and suburban areas of the city.
  • E. Osakako Station
    Osakako Station is a railway station in Osaka, Japan, serving the Osaka Metro Chūō Line and providing access to the Osaka Bay area’s attractions.
  • 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_69ab4ac739188190a112f42a5a69c951 completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abe02aa5948190a2e0bd9168232bd5 completed March 7, 2026, 8:22 a.m.
NED1 Entity disambiguation (via context triple) batch_69c8f2f8624c819090b3e197ec1c8891 completed March 29, 2026, 9:38 a.m.
Created at: March 6, 2026, 10:03 p.m.