Triple

T3225999
Position Surface form Disambiguated ID Type / Status
Subject Loulé E67623 entity
Predicate municipalSeat P15510 FINISHED
Object Loulé (town) 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 (town) | Statement: [Loulé, municipalSeat, Loulé (town)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Loulé (town)
Context triple: [Loulé, municipalSeat, Loulé (town)]
  • 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. Lourmarin, France
    Lourmarin, France is a picturesque Provençal village in the Luberon region of southeastern France, known for its Renaissance château, vibrant cultural life, and association with writer Albert Camus.
  • C. La Grande-Motte
    La Grande-Motte is a seaside resort town on France’s Mediterranean coast, noted for its distinctive modernist pyramid-shaped architecture and beaches.
  • D. Argelès-sur-Mer
    Argelès-sur-Mer is a coastal resort town in southern France known for its long Mediterranean beaches and proximity to the Pyrenees.
  • E. Lacanau
    Lacanau is a coastal resort town in southwestern France known for its Atlantic beaches, surfing, and large freshwater lake.
  • 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_69ad858c61888190a31196310d9b30b5 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69adaeb4cd3481908af8a2c9b6c0742d completed March 8, 2026, 5:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69b2625eaa708190b23ca6e575d664a2 completed March 12, 2026, 6:51 a.m.
Created at: March 8, 2026, 3:08 p.m.