Triple

T1368744
Position Surface form Disambiguated ID Type / Status
Subject Hunan Province E30061 entity
Predicate containsCity P294 FINISHED
Object Changde E76664 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: Changde | Statement: [Hunan Province, containsCity, Changde]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Changde
Context triple: [Hunan Province, containsCity, Changde]
  • A. Changde chosen
    Changde is a city in northwestern Hunan Province, China, historically significant as a major battleground during the Second Sino-Japanese War.
  • B. Hengyang
    Hengyang is a major industrial and transportation hub city in southern China, located along the Xiang River in the south of Hunan Province.
  • C. 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.
  • D. Zhuzhou
    Zhuzhou is a major industrial and transportation hub city in south-central China, known especially for its rail transit and manufacturing industries.
  • E. Changsha
    Changsha is the capital city of Hunan Province in south-central China, known as a historic cultural center and major regional economic hub.
  • 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_69a498f912008190a376a98b207b2071 completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c2d497f88190993d16a208ced43d completed March 1, 2026, 10:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad1c95b09881909e621ee55cdc7279 completed March 8, 2026, 6:52 a.m.
Created at: March 1, 2026, 7:57 p.m.