Triple

T13228752
Position Surface form Disambiguated ID Type / Status
Subject Puno Province E314952 entity
Predicate hasMajorCity P316 FINISHED
Object Puno E61910 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: Puno | Statement: [Puno Province, hasMajorCity, Puno]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Puno
Context triple: [Puno Province, hasMajorCity, Puno]
  • A. Puno chosen
    Puno is a city in southeastern Peru on the shores of Lake Titicaca, known as a cultural center of the Andean highlands and a gateway to the lake’s islands.
  • B. Paruro
    Paruro is a small town in the Cusco Region of Peru that serves as the administrative and political center of Paruro Province.
  • C. Cuyoño
    Cuyoño is an Austronesian language spoken primarily in the Cuyo Islands and parts of Palawan in the Philippines.
  • D. Juliaca
    Juliaca is a major commercial and transportation hub in southern Peru, known for its bustling markets and proximity to Lake Titicaca.
  • E. Colina
    Colina is a commune and city in central Chile known for its growing residential areas and proximity to Santiago in the Santiago Metropolitan Region.
  • 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_69d806affc688190a25b6ccc588e9c72 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98d3232d48190a3c792b025c596a6 completed April 10, 2026, 11:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69f70a3407388190bef886884cb75912 completed May 3, 2026, 8:41 a.m.
Created at: April 9, 2026, 9:21 p.m.