Triple

T14767088
Position Surface form Disambiguated ID Type / Status
Subject western Beijing E347024 entity
Predicate containsPart P35 FINISHED
Object Haidian District E89575 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: Haidian District | Statement: [western Beijing, containsPart, Haidian District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Haidian District
Context triple: [western Beijing, containsPart, Haidian District]
  • A. Haidian District chosen
    Haidian District is a major urban district in northwest Beijing known for its universities, technology hubs, and historic imperial gardens.
  • B. Haidian Subdistrict
    Haidian Subdistrict is the central urban area and seat of local government within Beijing’s Haidian District, known for its dense commercial and residential development.
  • C. Changping District
    Changping District is a suburban district in the northern part of Beijing, China, known for its historical sites and scenic mountainous landscapes.
  • D. Heping District
    Heping District is a central urban district of Tianjin, China, known for its commercial centers, historic architecture, and role as a core administrative and cultural area of the city.
  • E. Daxing District
    Daxing District is a rapidly developing suburban district in southern Beijing, China, known for hosting the major Beijing Daxing International Airport and large-scale urban expansion.
  • 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_69d822e8896c819091169882f9b20486 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69dec7f576c881909da70627f5897c94 completed April 14, 2026, 11:04 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0180bd1e5c8190a6a96581ce8a37de completed May 11, 2026, 7:09 a.m.
Created at: April 10, 2026, 1:30 a.m.