Triple

T5879434
Position Surface form Disambiguated ID Type / Status
Subject Serra de Tramuntana E130706 entity
Predicate contains P35 FINISHED
Object Valldemossa E156863 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: Valldemossa | Statement: [Serra de Tramuntana, contains, Valldemossa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Valldemossa
Context triple: [Serra de Tramuntana, contains, Valldemossa]
  • A. Valldemossa chosen
    Valldemossa is a picturesque mountain village on the Spanish island of Mallorca, renowned for its historic Carthusian monastery and scenic stone streets.
  • B. Sóller
    Sóller is a picturesque town in northwestern Mallorca, Spain, known for its historic tramway, citrus groves, and scenic setting in the Serra de Tramuntana mountains.
  • C. Cala d’Hort
    Cala d’Hort is a scenic beach on the southwest coast of Ibiza, famed for its views of the mystical Es Vedrà rock island and its sunsets.
  • D. Manresa
    Manresa is a historic city in Catalonia, Spain, known for its medieval architecture and significance as a religious and commercial center in the region.
  • E. Cala Millor
    Cala Millor is a popular resort town on the eastern coast of Mallorca, Spain, known for its long sandy beach and tourist amenities.
  • 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_69c0b12d9e348190b4baf171ce448d5b completed March 23, 2026, 3:19 a.m.
Created at: March 22, 2026, 3:57 p.m.