Triple

T706469
Position Surface form Disambiguated ID Type / Status
Subject Coquimbo Province E14109 entity
Predicate contains P35 FINISHED
Object Paihuano E34116 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: Paihuano | Statement: [Coquimbo Province, contains, Paihuano]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Paihuano
Context triple: [Coquimbo Province, contains, Paihuano]
  • A. Paihuano chosen
    Paihuano is a small town and commune in Chile’s Elqui Valley, known for its clear skies, pisco production, and astrotourism.
  • B. Guanggu
    Guanggu is a major high-tech development zone in Wuhan, China, known as an innovation hub for the optics and electronics industries.
  • C. Shiyan
    Shiyan is an industrial city in northwestern Hubei, China, best known as a center of automobile manufacturing and as a gateway to the nearby Wudang Mountains.
  • D. Huayu
    Huayu is a term used primarily in Singapore, Malaysia, and other overseas Chinese communities to refer to the standardized form of Mandarin Chinese used in education and media.
  • E. Mengjiang
    Mengjiang was a Japanese puppet state established in Inner Mongolia during the Second Sino-Japanese War and World War II.
  • 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_69a493494ec48190ae6751683625a9ba completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a54607f08190b3ee4805f2ea4b2f completed March 1, 2026, 8:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69a654dcbb688190ab997a3d31ec729a completed March 3, 2026, 3:26 a.m.
Created at: March 1, 2026, 7:36 p.m.