Triple

T7700797
Position Surface form Disambiguated ID Type / Status
Subject Furong District E174487 entity
Predicate partOf P40 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: [Furong District, partOf, Changsha]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Changsha
Context triple: [Furong District, partOf, 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_69c6995a72cc8190998e56daa6f8e453 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c70288d02c819093d6f0e47707d0a3 completed March 27, 2026, 10:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8d6ab0ab48190b273d07db6d74c33 completed March 29, 2026, 7:37 a.m.
Created at: March 27, 2026, 4:03 p.m.