Triple

T3166408
Position Surface form Disambiguated ID Type / Status
Subject Osaka Metro Midosuji Line E66221 entity
Predicate terminus P388 FINISHED
Object Esaka Station E430101 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: Esaka Station | Statement: [Osaka Metro Midosuji Line, terminus, Esaka Station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Esaka Station
Context triple: [Osaka Metro Midosuji Line, terminus, Esaka Station]
  • A. Esaka Station chosen
    Esaka Station is a major railway and subway hub in Suita, Osaka Prefecture, serving as an important commuter gateway between northern Osaka and central Osaka City.
  • B. Shindaita Station
    Shindaita Station is a railway station in Tokyo, Japan, serving passengers on the Keio Inokashira Line.
  • C. Imadegawa Station
    Imadegawa Station is an underground metro station on Kyoto’s subway network serving the area around Doshisha University and the Kyoto Imperial Palace.
  • D. Kujo Station
    Kujo Station is a subway station in Kyoto, Japan, served by the Kyoto Municipal Subway Karasuma Line.
  • E. Sannomiya Station
    Sannomiya Station is a major railway and transportation hub in central Kobe, Japan, serving multiple train and subway lines and providing access to the city's main commercial and tourist areas.
  • 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_69ad8585d7988190af37365331093ccd completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada643e3e481908f4526d66e36e150 completed March 8, 2026, 4:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69c98bd7f4dc8190975352b1eb790cae completed March 29, 2026, 8:30 p.m.
Created at: March 8, 2026, 3:06 p.m.