Triple

T13964051
Position Surface form Disambiguated ID Type / Status
Subject Linfen E335875 entity
Predicate capitalOf P204 FINISHED
Object Linfen City E335875 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: Linfen City | Statement: [Linfen, capitalOf, Linfen City]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Linfen City
Context triple: [Linfen, capitalOf, Linfen City]
  • A. Linfen chosen
    Linfen is a major industrial city in southern Shanxi Province, China, historically known for coal production and severe air pollution.
  • B. Jincheng
    Jincheng is an ancient name historically used for the Chinese city now known as Lanzhou, a key regional center along the Silk Road in Gansu Province.
  • C. Jincheng
    Jincheng is a prefecture-level city in southeastern Shanxi Province, China, known for its coal resources and heavy industry.
  • D. Jincheng
    Jincheng is the main urban township and administrative center of Kinmen County, located on the outlying Kinmen Islands governed by Taiwan.
  • E. Xinzhou
    Xinzhou is a prefecture-level city in northern China known for its historical sites and location within Shanxi Province’s coal-rich and culturally significant region.
  • 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_69d81c61f3508190aaf2ca0dc0002c59 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2e7e24f08190ba939a8044860033 completed April 14, 2026, 12:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcdef3f31c8190a2fc3eed316756d6 completed May 7, 2026, 6:50 p.m.
Created at: April 9, 2026, 10:18 p.m.