Triple

T13996767
Position Surface form Disambiguated ID Type / Status
Subject Fortunio Bonanova E336717 entity
Predicate placeOfBirth P1 FINISHED
Object Palma de Mallorca 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 de Mallorca | Statement: [Fortunio Bonanova, placeOfBirth, Palma de Mallorca]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Palma de Mallorca
Context triple: [Fortunio Bonanova, placeOfBirth, Palma de Mallorca]
  • A. 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.
  • B. Palma
    Palma is a Spanish-origin surname borne by various notable individuals across the Spanish-speaking world and beyond.
  • C. Lloret de Mar
    Lloret de Mar is a popular Mediterranean coastal resort town on Spain’s Costa Brava, known for its beaches, nightlife, and tourism.
  • D. Benidorm
    Benidorm is a major Spanish Mediterranean resort city famous for its skyscraper-lined beaches, vibrant nightlife, and mass tourism.
  • 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_69d81c645c5c8190b1fd16a285a1b78a completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2eb68ba88190bfaf10777d607bf3 completed April 14, 2026, 12:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69fbac9d4a54819091c7efbeb4dcc5f7 completed May 6, 2026, 9:03 p.m.
Created at: April 9, 2026, 10:19 p.m.