Triple

T14692705
Position Surface form Disambiguated ID Type / Status
Subject Handan Municipal Government E345072 entity
Predicate governs P760 FINISHED
Object hanshan district E395728 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: hanshan district | Statement: [Handan Municipal Government, governs, hanshan district]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: hanshan district
Context triple: [Handan Municipal Government, governs, hanshan district]
  • A. Hanshan District chosen
    Hanshan District is an urban administrative district of Handan City in Hebei Province, China, known for its role as part of the city's core built-up area.
  • B. Bagongshan District
    Bagongshan District is an urban administrative district of Huainan City in Anhui Province, China, known for its coal resources and industrial development.
  • C. Hongshan District
    Hongshan District is the central urban district and administrative seat of the prefecture-level city of Chifeng in Inner Mongolia, China.
  • D. Hongshan District
    Hongshan District is an urban district of Wuhan in Hubei Province, China, known for its educational institutions, technology parks, and major transportation hubs.
  • E. Honggu District
    Honggu District is an administrative urban district of Lanzhou in Gansu Province, China, known for its role in the city's industrial and resource-based development.
  • 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_69d822e34b348190ada4d1cdb6c7c226 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb585d46c81908d6964130914cec4 completed April 14, 2026, 9:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69fde18b4bdc8190b5daf05484de7cd8 completed May 8, 2026, 1:13 p.m.
Created at: April 10, 2026, 1:28 a.m.