Triple

T21959592
Position Surface form Disambiguated ID Type / Status
Subject A23 motorway (Portugal) E542287 entity
Predicate passesThroughRegion P3448 FINISHED
Object Ribatejo NE NERFINISHED

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: [A23 motorway (Portugal), passesThroughRegion, Ribatejo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ribatejo
Context triple: [A23 motorway (Portugal), passesThroughRegion, 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 (2 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_69e0c47fab1081908dc74a6545dbb051 completed April 16, 2026, 11:14 a.m.
NER Named-entity recognition batch_69f12454a290819094d4b56547816e3f completed April 28, 2026, 9:19 p.m.
Created at: April 16, 2026, 8 p.m.