Triple

T4050797
Position Surface form Disambiguated ID Type / Status
Subject Operation Go E84179 entity
Predicate capturedCity P8411 FINISHED
Object Changsha E29743 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: Changsha | Statement: [Operation Go, capturedCity, Changsha]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Changsha
Context triple: [Operation Go, capturedCity, Changsha]
  • A. Changsha chosen
    Changsha is the capital city of Hunan Province in south-central China, known as a historic cultural center and major regional economic hub.
  • B. Zhuzhou
    Zhuzhou is a major industrial and transportation hub city in south-central China, known especially for its rail transit and manufacturing industries.
  • C. Changde
    Changde is a city in northwestern Hunan Province, China, historically significant as a major battleground during the Second Sino-Japanese War.
  • D. Xiangtan
    Xiangtan is a prefecture-level city in central Hunan Province, China, known as an important industrial and commercial hub and for encompassing Shaoshan, the birthplace of Mao Zedong.
  • E. Hengyang
    Hengyang is a major industrial and transportation hub city in southern China, located along the Xiang River in the south of Hunan Province.
  • 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_69aed930bd5c819083e7dcc14fc44f69 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefb8413848190992e4b5f3b29b43c completed March 9, 2026, 4:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69b55659256081909154569cedd1694a completed March 14, 2026, 12:36 p.m.
Created at: March 9, 2026, 3:37 p.m.