Triple

T5668476
Position Surface form Disambiguated ID Type / Status
Subject Les Saintes E124913 entity
Predicate hasIsland P970 FINISHED
Object Redonde E99881 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: Redonde | Statement: [Les Saintes, hasIsland, Redonde]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Redonde
Context triple: [Les Saintes, hasIsland, Redonde]
  • A. Redondo
    Redondo is a municipality and town in Portugal’s Alentejo region, known for its wine production, traditional pottery, and well-preserved historic architecture.
  • B. Redonda chosen
    Redonda is a small, uninhabited rocky island in the Caribbean Sea that forms part of the nation of Antigua and Barbuda.
  • C. Alpedrete
    Alpedrete is a municipality in the Community of Madrid, Spain, known for its traditional stone quarries and residential character near the Sierra de Guadarrama.
  • D. Santarosa
    Santarosa was an Italian nobleman and revolutionary best known for his support of Greek independence and his role among the Philhellenes in the Greek War of Independence.
  • E. Toma
    Toma is a major Mande language spoken primarily in Guinea and neighboring West African countries.
  • 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_69c00828906881908966f270b8f130cf completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c023471f688190acec330596238a50 completed March 22, 2026, 5:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69c04dafb6b081909c5bf1527f185819 completed March 22, 2026, 8:14 p.m.
Created at: March 22, 2026, 3:43 p.m.