Triple

T5879593
Position Surface form Disambiguated ID Type / Status
Subject Palma de Mallorca Airport E130710 entity
Predicate locatedIn P40 FINISHED
Object Mallorca E23149 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: Mallorca | Statement: [Palma de Mallorca Airport, locatedIn, Mallorca]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mallorca
Context triple: [Palma de Mallorca Airport, locatedIn, Mallorca]
  • A. Mallorca chosen
    Mallorca is the largest of Spain’s Balearic Islands, renowned for its Mediterranean beaches, rugged limestone mountains, and historic towns such as Palma.
  • B. Minorca
    Minorca is one of Spain’s Balearic Islands in the Mediterranean Sea, known for its natural harbors, beaches, and historical strategic importance.
  • C. 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.
  • D. Balearic Islands
    The Balearic Islands are a Mediterranean archipelago and popular Spanish tourist destination known for islands such as Mallorca, Menorca, Ibiza, and Formentera.
  • E. Ibiza, Spain
    Ibiza, Spain is a Mediterranean island renowned for its vibrant nightlife, electronic music scene, and picturesque beaches.
  • 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_69c0085523688190bfd487479ce819e6 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c03633f0d88190b0ecf595cb28b783 completed March 22, 2026, 6:34 p.m.
NED1 Entity disambiguation (via context triple) batch_69c68564f0bc81909a310ec2026caa7f completed March 27, 2026, 1:25 p.m.
Created at: March 22, 2026, 3:57 p.m.