Triple

T16905353
Position Surface form Disambiguated ID Type / Status
Subject Huaraz E424546 entity
Predicate capitalOf P204 FINISHED
Object Huaraz Province NE NERFINISHED

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: Huaraz Province | Statement: [Huaraz, capitalOf, Huaraz Province]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Huaraz Province
Context triple: [Huaraz, capitalOf, Huaraz Province]
  • A. Huaraz Province chosen
    Huaraz Province is an administrative division in the Ancash Region of Peru, known for its capital city Huaraz and its proximity to the Cordillera Blanca mountain range.
  • B. Huarochirí Province
    Huarochirí Province is a highland administrative division of Peru’s Lima Region, known for its Andean landscapes, traditional Quechua-speaking communities, and pre-Hispanic cultural heritage.
  • C. Challapata Province
    Challapata Province is an administrative province in Bolivia’s Oruro Department, known for its high-altitude Andean landscapes and agricultural communities.
  • D. Hualgayoc Province
    Hualgayoc Province is an administrative division in northern Peru known for its high Andean terrain and significant mining activities.
  • E. Talara Province
    Talara Province is a coastal administrative division in northwestern Peru known for its oil industry and fishing activities.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d889da3e8c8190a2b118f383f0beac completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e3c8df454c8190898ebdd75985e51c completed April 18, 2026, 6:09 p.m.
Created at: April 10, 2026, 5:30 a.m.