Triple

T13572192
Position Surface form Disambiguated ID Type / Status
Subject Jieyang E324190 entity
Predicate hasDistrict P459 FINISHED
Object Jiedong District E1101420 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: Jiedong District | Statement: [Jieyang, hasDistrict, Jiedong District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jiedong District
Context triple: [Jieyang, hasDistrict, Jiedong District]
  • A. Jiedong District chosen
    Jiedong District is an administrative district of Jieyang in Guangdong Province, China, known for its role in the region’s economic and cultural activities.
  • B. Jianhua District
    Jianhua District is a central urban district of Qiqihar City in Heilongjiang Province, northeastern China.
  • C. Daiyue District
    Daiyue District is an administrative district under the jurisdiction of Tai'an City in Shandong Province, China, known for encompassing part of the Mount Tai scenic area.
  • D. Zhanggong District
    Zhanggong District is the central urban district and administrative, economic, and cultural core of Ganzhou in Jiangxi Province, China.
  • E. Jiawang District
    Jiawang District is an administrative district under the jurisdiction of Xuzhou in Jiangsu Province, eastern China, known historically for its coal mining 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_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_69fd7a2ae47881909e0e6c23473a9e1c completed May 8, 2026, 5:52 a.m.
Created at: April 9, 2026, 9:48 p.m.