Triple

T15570361
Position Surface form Disambiguated ID Type / Status
Subject Beiras E374222 entity
Predicate borders P224 FINISHED
Object Ribatejo E123602 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: Ribatejo | Statement: [Beiras, borders, Ribatejo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ribatejo
Context triple: [Beiras, borders, Ribatejo]
  • A. Ribatejo chosen
    Ribatejo is a historical province in central Portugal known for its fertile plains, agriculture, and traditional bullfighting culture.
  • B. Potrerillos
    Potrerillos is a town and municipality located in the Cortés Department of northwestern Honduras.
  • C. Riparbella
    Riparbella is a small Tuscan hill town in central Italy, known for its rural landscapes, vineyards, and traditional agricultural economy.
  • D. Turrubares
    Turrubares is a rural canton in Costa Rica known for its mountainous landscapes, agricultural activities, and low population density.
  • E. Negrete
    Negrete is a small town and commune in Chile’s Biobío Region, known for its rural character and location near the Biobío River.
  • 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_69e04e1de0488190b3639fc25f79d343 completed April 16, 2026, 2:49 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff5f30e48881908b30a71796fe0d72 completed May 9, 2026, 4:22 p.m.
Created at: April 10, 2026, 4:10 a.m.