Triple

T7984306
Position Surface form Disambiguated ID Type / Status
Subject Battle of Changping E185651 entity
Predicate location P40 FINISHED
Object Changping E77195 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: Changping | Statement: [Battle of Changping, location, Changping]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Changping
Context triple: [Battle of Changping, location, Changping]
  • A. Lingang
    Lingang is a rapidly developing industrial and high-tech district in Shanghai, China, known for hosting major manufacturing facilities such as Tesla’s Gigafactory Shanghai.
  • B. Yizhuang
    Yizhuang is a rapidly developing suburban area in southeastern Beijing known for its economic and technological development zone and growing residential communities.
  • C. Changping District chosen
    Changping District is a suburban district in the northern part of Beijing, China, known for its historical sites and scenic mountainous landscapes.
  • D. Daoxin
    Daoxin was an influential early Chinese Chan (Zen) Buddhist master traditionally regarded as the Fourth Patriarch, known for helping shape the school’s meditative and doctrinal foundations.
  • E. Miyun District
    Miyun District is a suburban district in northeastern Beijing, China, known for its scenic reservoirs, mountains, and sections of the Great Wall.
  • 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_69ca829a2cfc819083d591d58ec04075 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3c2b543c81909b82bc478d579e0b completed March 31, 2026, 3:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc63b96ed48190b752865ef3855e46 completed April 1, 2026, 12:15 a.m.
Created at: March 30, 2026, 5:15 p.m.