Triple

T6074154
Position Surface form Disambiguated ID Type / Status
Subject Chengdu Plain E135356 entity
Predicate containsCity P294 FINISHED
Object Mianyang E268218 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: Mianyang | Statement: [Chengdu Plain, containsCity, Mianyang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mianyang
Context triple: [Chengdu Plain, containsCity, Mianyang]
  • A. Mianyang chosen
    Mianyang is a major city in southwestern China known as an important industrial and technological center within Sichuan Province.
  • B. Nanchong
    Nanchong is a major city in northeastern Sichuan Province, China, known as a regional transportation and economic hub with a long historical and cultural heritage.
  • C. Deyang
    Deyang is an industrial city in southwestern China known for its heavy machinery manufacturing and location near Chengdu in Sichuan Province.
  • D. Langzhong
    Langzhong is an ancient county-level city in Sichuan, China, renowned for its well-preserved historic old town and traditional architecture along the Jialing River.
  • E. Yibin
    Yibin is a historic prefecture-level city in southwestern China known as the "First City on the Yangtze River," where the Jinsha and Min rivers converge to form the Yangtze.
  • 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_69c00879e8048190b690717d19c5bc03 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c0575b9bc08190a78b3082b9ccf00c completed March 22, 2026, 8:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69c20d4e28b48190bb44675c5c035bd3 completed March 24, 2026, 4:04 a.m.
Created at: March 22, 2026, 4:11 p.m.