Triple

T10241672
Position Surface form Disambiguated ID Type / Status
Subject María Elena E243607 entity
Predicate hasNearbyCity P350 FINISHED
Object Calama E34573 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: Calama | Statement: [María Elena, hasNearbyCity, Calama]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Calama
Context triple: [María Elena, hasNearbyCity, Calama]
  • A. Calama chosen
    Calama is a city in northern Chile known as a key mining center and gateway to the Atacama Desert.
  • B. Puerto Varas
    Puerto Varas is a picturesque lakeside city in southern Chile’s Los Lagos Region, known for its German-influenced architecture and views of the Osorno and Calbuco volcanoes.
  • C. Pichilemu
    Pichilemu is a coastal Chilean city renowned as a major surfing destination and seaside resort on the Pacific Ocean.
  • D. Puerto Valdivia
    Puerto Valdivia is a small riverside town in northern Colombia known for its location along the Cauca River and its role as a local transport and trading point.
  • E. Melipeuco
    Melipeuco is a small Andean foothill town and commune in southern Chile known for its proximity to Conguillío National Park and the Llaima volcano.
  • 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_69d381b0f97c819085c9b45799a5fb7c completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d21f2ae0819098ac60c828dc9cae completed April 7, 2026, 9:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69d6f780c7808190993e7c37cb4d18a3 completed April 9, 2026, 12:49 a.m.
Created at: April 6, 2026, 11:24 a.m.