Triple

T13572191
Position Surface form Disambiguated ID Type / Status
Subject Jieyang E324190 entity
Predicate hasDistrict P459 FINISHED
Object Rongcheng District E1099773 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: Rongcheng District | Statement: [Jieyang, hasDistrict, Rongcheng District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rongcheng District
Context triple: [Jieyang, hasDistrict, Rongcheng District]
  • A. Rongcheng District chosen
    Rongcheng District is the central urban district and administrative seat of Jieyang City in Guangdong Province, China.
  • B. Yingquan District
    Yingquan District is an urban administrative district of the city of Fuyang in Anhui Province, China.
  • C. Runzhou District
    Runzhou District is a central urban district of Zhenjiang in Jiangsu Province, China, known for its administrative, commercial, and historical significance within the city.
  • D. Yongnian District
    Yongnian District is an administrative district under the jurisdiction of Handan City in Hebei Province, China, known for its historical and cultural significance.
  • E. Licheng District
    Licheng District is a central urban district of Quanzhou in Fujian Province, China, known for its historic architecture and cultural heritage.
  • 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_69d80769100c819099111274614f5ed2 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbb0106cb48190b20eb9bda131a68a completed April 12, 2026, 2:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd6d6fde508190865a8e3e391fdf5e completed May 8, 2026, 4:58 a.m.
Created at: April 9, 2026, 9:48 p.m.