Triple

T17463397
Position Surface form Disambiguated ID Type / Status
Subject Rebel Air Force E425214 entity
Predicate operationalArea P794 FINISHED
Object Balearic Islands NE NERFINISHED

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: Balearic Islands | Statement: [Rebel Air Force, operationalArea, Balearic Islands]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Balearic Islands
Context triple: [Rebel Air Force, operationalArea, Balearic Islands]
  • A. Balearic Islands chosen
    The Balearic Islands are a Mediterranean archipelago and popular Spanish tourist destination known for islands such as Mallorca, Menorca, Ibiza, and Formentera.
  • B. Canary Islands
    The Canary Islands are a Spanish archipelago off the northwest coast of Africa, known for their volcanic landscapes, subtropical climate, and popularity as a tourist destination.
  • C. Mallorca
    Mallorca is the largest of Spain’s Balearic Islands, renowned for its Mediterranean beaches, rugged limestone mountains, and historic towns such as Palma.
  • 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. Maiorca
    Maiorca is a civil parish in the municipality of Figueira da Foz, located in the Coimbra District of central Portugal.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d889dbc2e88190b18ea6115e819258 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e451a4c36c81909c7c4b1b0d976921 completed April 19, 2026, 3:53 a.m.
Created at: April 10, 2026, 5:47 a.m.