Triple

T3530407
Position Surface form Disambiguated ID Type / Status
Subject Shinagawa E74645 entity
Predicate hasRailwayHub P1071 FINISHED
Object Ōsaki Station E147524 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: Ōsaki Station | Statement: [Shinagawa, hasRailwayHub, Ōsaki Station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ōsaki Station
Context triple: [Shinagawa, hasRailwayHub, Ōsaki Station]
  • A. Osaki Station chosen
    Osaki Station is a major railway hub in Tokyo, Japan, serving multiple JR East lines and connecting central Tokyo with surrounding suburban areas.
  • B. Hakata Station
    Hakata Station is the main railway hub of Fukuoka and a major Shinkansen and regional train terminal in Kyushu, Japan.
  • C. Wakayama Station
    Wakayama Station is a major railway hub in Wakayama City, Japan, serving multiple JR West lines and connecting the region to the wider Kansai area.
  • D. Daigo Station
    Daigo Station is a subway station in Kyoto, Japan, serving the Kyoto Municipal Subway network and providing access to the Daigo area and nearby cultural sites.
  • E. 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.
  • 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_69ad85d1a3948190931fd1ea1f49717b completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adbc9764a881908aa8d25dc9adf59e completed March 8, 2026, 6:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69cfeaaf9ea0819091bd0981068e5a72 completed April 3, 2026, 4:28 p.m.
Created at: March 8, 2026, 3:19 p.m.