Triple

T13851106
Position Surface form Disambiguated ID Type / Status
Subject Jincheng E332941 entity
Predicate hasUrbanArea P316 FINISHED
Object Jincheng urban district E332941 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: Jincheng urban district | Statement: [Jincheng, hasUrbanArea, Jincheng urban district]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jincheng urban district
Context triple: [Jincheng, hasUrbanArea, Jincheng urban district]
  • A. Wuzhong District
    Wuzhong District is an urban district of Suzhou in Jiangsu Province, China, known for its historic canals, classical gardens, and rapidly developing economy.
  • B. Hecheng District
    Hecheng District is the central urban district and administrative seat of Huaihua in Hunan Province, China.
  • C. Datong District
    Datong District is an urban administrative district under the jurisdiction of Huainan City in Anhui Province, China, known for its role in the region’s coal industry and urban development.
  • D. Jincheng
    Jincheng is the main urban township and administrative center of Kinmen County, located on the outlying Kinmen Islands governed by Taiwan.
  • E. Jincheng chosen
    Jincheng is a prefecture-level city in southeastern Shanxi Province, China, known for its coal resources and heavy industry.
  • 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_69d81c5ba13c8190839315f54768acfd completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de02d8fb788190baef7537be2baecb completed April 14, 2026, 9:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7c0f73838819085d6f052c00fc494 completed May 3, 2026, 9:41 p.m.
Created at: April 9, 2026, 10:14 p.m.