Triple

T1738643
Position Surface form Disambiguated ID Type / Status
Subject Fóia E37978 entity
Predicate locatedIn P40 FINISHED
Object Serra de Monchique E37978 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: Serra de Monchique | Statement: [Fóia, locatedIn, Serra de Monchique]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Serra de Monchique
Context triple: [Fóia, locatedIn, Serra de Monchique]
  • A. Monchique chosen
    Monchique is a mountainous spa town in southern Portugal known for its lush forests, thermal springs, and panoramic views over the Algarve region.
  • B. Sierra de la Victoria
    Sierra de la Victoria is a mountain range located on the Baja California Peninsula in northwestern Mexico.
  • C. Sierra de Guadarrama
    Sierra de Guadarrama is a prominent mountain range in central Spain, forming part of the Central System and serving as a natural border between the Community of Madrid and Castile and León.
  • D. Sierra de San Javier
    Sierra de San Javier is a mountain range on Mexico’s Baja California Peninsula known for its rugged terrain, desert landscapes, and proximity to historic mission sites.
  • E. Monte Gordo
    Monte Gordo is a popular seaside resort town in Portugal’s Algarve region, known for its wide sandy beaches and tourism-focused amenities.
  • 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_69a8861cc6ac8190ac0b2e31ccf62851 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa63c35aec8190b5c19ace5524173f completed March 6, 2026, 5:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69ada0dbc7c081909d637c5a482389ef completed March 8, 2026, 4:16 p.m.
Created at: March 4, 2026, 7:30 p.m.