Triple

T11566791
Position Surface form Disambiguated ID Type / Status
Subject Deyang E274272 entity
Predicate hasChineseName P4878 FINISHED
Object 德阳 E274272 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: 德阳 | Statement: [Deyang, hasChineseName, 德阳]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: 德阳
Context triple: [Deyang, hasChineseName, 德阳]
  • A. Deyang chosen
    Deyang is an industrial city in southwestern China known for its heavy machinery manufacturing and location near Chengdu in Sichuan Province.
  • B. Mianyang
    Mianyang is a major city in southwestern China known as an important industrial and technological center within Sichuan Province.
  • C. 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.
  • D. Dujiangyan City
    Dujiangyan City is a county-level city in Sichuan Province, China, best known as the home of the ancient Dujiangyan Irrigation System, a UNESCO World Heritage Site.
  • E. 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.
  • 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_69d6aae5ac3c81908d2b0a3a665665b2 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d88dd4305c8190ac5ff490b6b63e12 completed April 10, 2026, 5:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69e6e8c9a22c8190812c64b9f305ae99 completed April 21, 2026, 3:02 a.m.
Created at: April 8, 2026, 9:37 p.m.