Triple

T8053027
Position Surface form Disambiguated ID Type / Status
Subject Xinyu E187720 entity
Predicate shortName P43 FINISHED
Object Xinyu City E187720 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: Xinyu City | Statement: [Xinyu, shortName, Xinyu City]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Xinyu City
Context triple: [Xinyu, shortName, Xinyu City]
  • A. Zunhua City
    Zunhua City is a county-level city in northeastern Hebei Province, China, known for its historical sites and administrative affiliation with the prefecture-level city of Tangshan.
  • B. Longyan
    Longyan is a prefecture-level city in western Fujian Province, China, known for its Hakka culture, mountainous landscapes, and historic tulou earthen dwellings.
  • C. Xinyu chosen
    Xinyu is a prefecture-level industrial city located in central Jiangxi Province in southeastern China.
  • D. Leiyang City
    Leiyang City is a county-level city administered by Hengyang in Hunan Province, China, known for its long history and role as a regional industrial and transportation hub.
  • E. Enshi City
    Enshi City is a county-level city in southwestern Hubei Province, China, known for its mountainous karst landscapes and role as a cultural center for the Tujia and Miao ethnic groups.
  • 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_69ca82b15e948190a62fd7af5218426a completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3f7c425c8190aa1b2f534afeb58c completed March 31, 2026, 3:29 a.m.
NED1 Entity disambiguation (via context triple) batch_69ce38eaf93481908939e770f0dda7f5 completed April 2, 2026, 9:37 a.m.
Created at: March 30, 2026, 5:25 p.m.