Triple

T428633
Position Surface form Disambiguated ID Type / Status
Subject Praia da Falésia E9664 entity
Predicate locatedInMunicipality P40 FINISHED
Object Loulé E67623 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: Loulé | Statement: [Praia da Falésia, locatedInMunicipality, Loulé]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Loulé
Context triple: [Praia da Falésia, locatedInMunicipality, Loulé]
  • A. Loulé chosen
    Loulé is a historic market town and municipality in southern Portugal known for its traditional architecture, lively festivals, and role as a cultural and commercial center in the Algarve region.
  • B. Saint-Tropez
    Saint-Tropez is a coastal town on the French Riviera, famed as a glamorous Mediterranean resort and former artists’ haven.
  • C. Olona
    The Olona is a river in northern Italy that flows through the Lombardy region, including the city of Milan.
  • D. Antibes
    Antibes is a historic resort town on the French Riviera known for its Mediterranean coastline, old town, and association with artists such as Pablo Picasso.
  • E. Toulon
    Toulon is a major port city on France’s Mediterranean coast that serves as the principal base of the French Navy.
  • 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_69a2e801e1d48190b505d1dd336b52ac completed Feb. 28, 2026, 1:05 p.m.
NER Named-entity recognition batch_69a2eeecb64c81908c5c83ef7c0181e6 completed Feb. 28, 2026, 1:34 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7a3a260888190b89e90c1da061733 completed March 4, 2026, 3:14 a.m.
Created at: Feb. 28, 2026, 1:11 p.m.