Triple

T8929759
Position Surface form Disambiguated ID Type / Status
Subject SEAT Ibiza E212621 entity
Predicate namedAfter P63 FINISHED
Object Ibiza E23828 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: Ibiza | Statement: [SEAT Ibiza, namedAfter, Ibiza]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ibiza
Context triple: [SEAT Ibiza, namedAfter, Ibiza]
  • A. Mallorca
    Mallorca is the largest of Spain’s Balearic Islands, renowned for its Mediterranean beaches, rugged limestone mountains, and historic towns such as Palma.
  • B. Formentera
    Formentera is a small Balearic Island in the Mediterranean Sea, renowned for its pristine white-sand beaches, crystal-clear waters, and laid-back atmosphere.
  • C. Ibiza, Spain chosen
    Ibiza, Spain is a Mediterranean island renowned for its vibrant nightlife, electronic music scene, and picturesque beaches.
  • D. Minorca
    Minorca is one of Spain’s Balearic Islands in the Mediterranean Sea, known for its natural harbors, beaches, and historical strategic importance.
  • E. Pla de Mallorca
    Pla de Mallorca is a central inland comarca (county) on the island of Mallorca in Spain, characterized by its rural landscapes, traditional villages, and agricultural economy.
  • 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_69ca8395c438819087d7cb844ab5990c completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc6676d5d881908ce78cbb5561a68b completed April 1, 2026, 12:27 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfc93587b081908e23c2a8c01b9516 completed April 3, 2026, 2:05 p.m.
Created at: March 30, 2026, 6:57 p.m.