Triple

T15498363
Position Surface form Disambiguated ID Type / Status
Subject Tieling E378881 entity
Predicate capitalOf P204 FINISHED
Object Tieling City E378881 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: Tieling City | Statement: [Tieling, capitalOf, Tieling City]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tieling City
Context triple: [Tieling, capitalOf, Tieling City]
  • A. Tieling chosen
    Tieling is a prefecture-level city in northeastern China known for its coal resources and location within Liaoning Province.
  • B. Liaoyuan
    Liaoyuan is a prefecture-level city in northeastern China known for its coal mining history and location in the central part of Jilin Province.
  • C. Yingkou
    Yingkou is a coastal port city in northeastern China’s Liaoning Province, known as an important industrial and shipping hub on the Bohai Sea.
  • D. Jinzhou
    Jinzhou is a prefecture-level port city in southwestern Liaoning Province, northeastern China, known for its industrial base and coastal location on the Bohai Sea.
  • E. Fuxin
    Fuxin is a prefecture-level city in northeastern China known historically for its coal mining industry and location in western Liaoning Province.
  • 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_69d85cd53a7c819080f5b9042c4c199e completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e03fb0aee081909db1c54349ec8492 completed April 16, 2026, 1:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff3667a53c81908be789f99e580265 completed May 9, 2026, 1:28 p.m.
Created at: April 10, 2026, 3:53 a.m.