Triple

T21544933
Position Surface form Disambiguated ID Type / Status
Subject Palmesana E531596 entity
Predicate usedIn P98 FINISHED
Object Mallorca 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: Mallorca | Statement: [Palmesana, usedIn, Mallorca]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mallorca
Context triple: [Palmesana, usedIn, 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. Maiorca
    Maiorca is a civil parish in the municipality of Figueira da Foz, located in the Coimbra District of central Portugal.
  • C. Minorca
    Minorca is one of Spain’s Balearic Islands in the Mediterranean Sea, known for its natural harbors, beaches, and historical strategic importance.
  • D. 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.
  • E. 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.
  • 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_69e0c45f17148190949c330ab9c27706 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69eeb58e38808190888f3501cf4fff7c completed April 27, 2026, 1:02 a.m.
Created at: April 16, 2026, 6:28 p.m.