Triple

T11988880
Position Surface form Disambiguated ID Type / Status
Subject Catalan Countries E285352 entity
Predicate hasMajorCity P316 FINISHED
Object Palma E144499 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: Palma | Statement: [Catalan Countries, hasMajorCity, Palma]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Palma
Context triple: [Catalan Countries, hasMajorCity, Palma]
  • A. Palma
    Palma is a Spanish-origin surname borne by various notable individuals across the Spanish-speaking world and beyond.
  • B. Palma de Mallorca chosen
    Palma de Mallorca is the historic coastal city and major tourist destination that serves as the political, cultural, and economic center of Spain’s Balearic Islands.
  • C. Mahón
    Mahón is the principal city and administrative center of the Spanish Balearic island of Menorca, known for its large natural harbor and historic architecture.
  • D. Denia
    Denia is a coastal city on Spain’s Costa Blanca known for its historic castle, Mediterranean beaches, and vibrant port.
  • E. Marbella
    Marbella is a popular resort city on Spain’s Costa del Sol, known for its Mediterranean beaches, luxury marinas, upscale nightlife, and historic old town.
  • 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_69d6ab44a77c8190a652f4b27164e4ef completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d903ae28708190a826bad1624343eb completed April 10, 2026, 2:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69f472492ebc8190b064e691bb70e356 completed May 1, 2026, 9:28 a.m.
Created at: April 8, 2026, 9:46 p.m.