Triple

T12256042
Position Surface form Disambiguated ID Type / Status
Subject Changzhou Railway Station E292102 entity
Predicate connectsTo P845 FINISHED
Object Hefei E17536 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: Hefei | Statement: [Changzhou Railway Station, connectsTo, Hefei]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hefei
Context triple: [Changzhou Railway Station, connectsTo, Hefei]
  • A. Hefei chosen
    Hefei is the capital and largest city of Anhui Province in eastern China, known as a major industrial, scientific, and educational center.
  • B. Wuhu
    Wuhu is a major industrial and transportation hub city in southeastern Anhui Province, eastern China, situated on the lower reaches of the Yangtze River.
  • C. Chuzhou
    Chuzhou is a prefecture-level city in eastern China known for its location near the Yangtze River and its role as a regional transportation and agricultural hub in Anhui Province.
  • D. Anqing
    Anqing is a prefecture-level city in southwestern Anhui Province, China, known historically as a regional political and military center along the Yangtze River.
  • E. Chaohu City
    Chaohu City is a county-level city in Anhui Province, China, known for its proximity to the large freshwater Chaohu Lake and its role in regional agriculture and fisheries.
  • 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_69d6ab67950c8190be08450a06228c4b completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d91cc9dd5081908880061d52351850 completed April 10, 2026, 3:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69f61e63da6081908840b1e37fd39b88 completed May 2, 2026, 3:55 p.m.
Created at: April 8, 2026, 9:52 p.m.