Triple

T21544939
Position Surface form Disambiguated ID Type / Status
Subject Palmesana E531596 entity
Predicate cityDemonymOf P191 FINISHED
Object Palma de 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: Palma de Mallorca | Statement: [Palmesana, cityDemonymOf, Palma de Mallorca]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Palma de Mallorca
Context triple: [Palmesana, cityDemonymOf, 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. Palma
    Palma is a coastal town in northern Mozambique’s Cabo Delgado Province, known for its proximity to major offshore natural gas projects and for being heavily affected by recent insurgent violence.
  • D. 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.
  • E. Benidorm
    Benidorm is a major Spanish Mediterranean resort city famous for its skyscraper-lined beaches, vibrant nightlife, and mass tourism.
  • 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.