Triple

T3796402
Position Surface form Disambiguated ID Type / Status
Subject Daxing District E89779 entity
Predicate borders P224 FINISHED
Object Chaoyang District E68683 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: Chaoyang District | Statement: [Daxing District, borders, Chaoyang District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chaoyang District
Context triple: [Daxing District, borders, Chaoyang District]
  • A. Chaoyang District chosen
    Chaoyang District is a major urban district in Beijing known for its modern business centers, diplomatic quarter, and prominent Olympic venues.
  • B. Chaoyang
    Chaoyang is a prefecture-level city in western Liaoning Province, China, known for its historical sites and role as a regional transportation and agricultural center.
  • C. 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.
  • D. Fengtai District
    Fengtai District is an urban district in southwestern Beijing, China, known for its mix of residential, industrial, and historical areas, including the site of the Marco Polo Bridge.
  • E. Haidian District
    Haidian District is a major urban district in northwest Beijing known for its universities, technology hubs, and historic imperial gardens.
  • 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_69aed9597d6881909b6ee3b9de859223 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aee79f09bc8190b7514a11a030eba5 completed March 9, 2026, 3:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69be67a7c3188190bc5d75eb2efb653d completed March 21, 2026, 9:40 a.m.
Created at: March 9, 2026, 3:15 p.m.