Triple

T11230226
Position Surface form Disambiguated ID Type / Status
Subject Moxico Province E265799 entity
Predicate hasCity P316 FINISHED
Object Luena E902807 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: Luena | Statement: [Moxico Province, hasCity, Luena]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Luena
Context triple: [Moxico Province, hasCity, Luena]
  • A. Luena chosen
    Luena is a city in eastern Angola that served as a significant site during the Angolan Civil War and later became known as the burial place of UNITA leader Jonas Savimbi.
  • B. Cuencamé
    Cuencamé is a municipality and town in the Mexican state of Durango, historically part of the colonial province of Nueva Vizcaya.
  • C. Montalva
    Montalva is a Spanish-language surname notably associated with Chilean president Eduardo Frei Montalva.
  • D. Montefrío
    Montefrío is a picturesque Andalusian town in southern Spain, renowned for its dramatic hilltop setting, whitewashed houses, and historic church and castle overlooking surrounding olive groves.
  • E. Peñafiel
    Peñafiel is a historic town in Spain renowned for its medieval castle and wine-making tradition in the Ribera del Duero 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_69d6aac656d48190b275efaa7d6074ee completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e900fbcc8190a3177f8a73564433 completed April 9, 2026, 5:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69e4cc4c630c8190a5e43c2108dfb50d completed April 19, 2026, 12:36 p.m.
Created at: April 8, 2026, 9:30 p.m.