Triple

T13302565
Position Surface form Disambiguated ID Type / Status
Subject Taiyuan South Railway Station E316849 entity
Predicate locatedIn P40 FINISHED
Object Xiaodian District E355687 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: Xiaodian District | Statement: [Taiyuan South Railway Station, locatedIn, Xiaodian District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Xiaodian District
Context triple: [Taiyuan South Railway Station, locatedIn, Xiaodian District]
  • A. Xiaodian District chosen
    Xiaodian District is an urban district of Taiyuan, the capital city of Shanxi Province in northern China, known for its residential areas and growing commercial development.
  • B. Caidian District
    Caidian District is an administrative district in the western part of Wuhan, China, known for its rapid urban development and integration into the city’s metro network.
  • C. Chenghua District
    Chenghua District is an urban district of Chengdu, China, best known internationally as the home of the Chengdu Research Base of Giant Panda Breeding.
  • D. Longquanyi District
    Longquanyi District is an urban district of Chengdu in Sichuan Province, China, known for its rapid development and sports facilities.
  • E. Huadu District
    Huadu District is a suburban district in the northern part of Guangzhou, China, known for its growing urban development and transportation links, including metro and rail connections.
  • 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_69d806b40ab4819094adf6c374f4811a completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d990a60eb08190bf0dc098ca7dc342 completed April 11, 2026, 12:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69fcb6419a3c8190bfaeab65f3909474 completed May 7, 2026, 3:56 p.m.
Created at: April 9, 2026, 9:28 p.m.