Triple

T4050798
Position Surface form Disambiguated ID Type / Status
Subject Operation Go E84179 entity
Predicate capturedCity P8411 FINISHED
Object Hengyang E168458 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: Hengyang | Statement: [Operation Go, capturedCity, Hengyang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hengyang
Context triple: [Operation Go, capturedCity, Hengyang]
  • A. Hengyang chosen
    Hengyang is a major industrial and transportation hub city in southern China, located along the Xiang River in the south of Hunan Province.
  • B. Huaihua
    Huaihua is a prefecture-level city in southwestern Hunan Province, China, known as a regional transportation hub and home to several ethnic minority communities.
  • C. Yongzhou
    Yongzhou is a prefecture-level city in southern Hunan Province, China, known for its long history and location at the confluence of the Xiang and Xiao rivers.
  • D. Changde
    Changde is a city in northwestern Hunan Province, China, historically significant as a major battleground during the Second Sino-Japanese War.
  • E. Chenzhou
    Chenzhou is a prefecture-level city in southern Hunan Province, China, known as a regional transport hub and for its rich mineral resources and scenic mountainous landscapes.
  • 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_69b56b501c008190ac115240328c6fc9 completed March 14, 2026, 2:06 p.m.
Created at: March 9, 2026, 3:37 p.m.