Triple

T15081478
Position Surface form Disambiguated ID Type / Status
Subject Huzhou E360154 entity
Predicate hasCounty P285 FINISHED
Object Deqing County E1052088 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: Deqing County | Statement: [Huzhou, hasCounty, Deqing County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Deqing County
Context triple: [Huzhou, hasCounty, Deqing County]
  • A. Deqing County chosen
    Deqing County is a county in northern Zhejiang Province, China, known for its scenic landscapes and popular tourist destinations such as the Moganshan mountain resort area.
  • B. Wuzhai County
    Wuzhai County is an administrative county in Shanxi Province, China, known for its mountainous terrain and location in the northern part of the province.
  • C. Xuyong County
    Xuyong County is an administrative county in Sichuan Province, China, governed by the prefecture-level city of Luzhou.
  • D. Tonglu County
    Tonglu County is a scenic county in Zhejiang Province, China, known for its picturesque river landscapes, karst mountains, and growing tourism industry.
  • E. Qianxi County
    Qianxi County is an administrative county under the jurisdiction of Tangshan City in Hebei Province, northern China, known for its mountainous terrain and historical sites.
  • 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_69d85a035aa88190b52a139d3a1b7b6d completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0027450a48190a84588b6aaf84ebf completed April 15, 2026, 9:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69fee5e2b2188190b96807ca6442fb01 completed May 9, 2026, 7:44 a.m.
Created at: April 10, 2026, 3:03 a.m.