Triple

T18588435
Position Surface form Disambiguated ID Type / Status
Subject Fuzhou dialect E454297 entity
Predicate spokenIn P2266 FINISHED
Object Changle District NE NERFINISHED

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: Changle District | Statement: [Fuzhou dialect, spokenIn, Changle District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Changle District
Context triple: [Fuzhou dialect, spokenIn, Changle District]
  • A. Changle District chosen
    Changle District is a coastal urban district of Fuzhou in Fujian Province, China, known for its maritime economy and proximity to Fuzhou Changle International Airport.
  • B. Lucheng District
    Lucheng District is the central urban district and administrative seat of Changzhi, a prefecture-level city in Shanxi Province, China.
  • C. Lucheng District
    Lucheng District is the central urban district and administrative, commercial, and cultural core of Wenzhou in Zhejiang Province, China.
  • D. Zhanqian District
    Zhanqian District is an urban administrative district under the jurisdiction of Yingkou City in Liaoning Province, China.
  • E. Hecheng District
    Hecheng District is the central urban district and administrative seat of Huaihua in Hunan Province, China.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8d38ae7e081908a98df1251842402 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e545b3e564819088e60fc25d1976f0 completed April 19, 2026, 9:14 p.m.
Created at: April 10, 2026, 11:44 a.m.