Triple

T15567950
Position Surface form Disambiguated ID Type / Status
Subject Oleiros E374163 entity
Predicate hasAdministrativeCenter P1474 FINISHED
Object Oleiros (town) E1133978 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: Oleiros (town) | Statement: [Oleiros, hasAdministrativeCenter, Oleiros (town)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oleiros (town)
Context triple: [Oleiros, hasAdministrativeCenter, Oleiros (town)]
  • A. Oleiros Municipality chosen
    Oleiros Municipality is a local administrative region in central Portugal known for its rural landscapes, traditional villages, and forested mountain terrain.
  • B. Olivar de Quintos
    Olivar de Quintos is a metro station in the Seville metropolitan area that serves as one of the termini of the Seville Metro network.
  • C. Orejon (Orejón)
    Orejón (Orejon) is an indigenous Tucanoan language spoken by the Orejón people of the Peruvian Amazon.
  • D. Arraiolos Municipality
    Arraiolos Municipality is a local administrative region in Portugal known for its historic town and traditional hand-embroidered wool rugs called Arraiolos carpets.
  • E. Olivar de los Padres
    Olivar de los Padres is a residential neighborhood in the Álvaro Obregón borough of Mexico City, known for its hilly terrain and mix of urban and green areas.
  • 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_69d85ccd575081908909b71a3f3e3a61 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04dde90b081908284d9258d4462e3 completed April 16, 2026, 2:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff4c4219a081909acca9f783ecd44b completed May 9, 2026, 3:01 p.m.
Created at: April 10, 2026, 4:10 a.m.