Triple

T11879549
Position Surface form Disambiguated ID Type / Status
Subject La Besurta trailhead E282619 entity
Predicate hasViewOf P854 FINISHED
Object Maladeta E951949 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: Maladeta | Statement: [La Besurta trailhead, hasViewOf, Maladeta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maladeta
Context triple: [La Besurta trailhead, hasViewOf, Maladeta]
  • A. Maladeta chosen
    Maladeta is a prominent peak in the central Pyrenees of Spain, known for its glaciated massif and proximity to Aneto, the highest mountain in the range.
  • B. Malad
    Malad is a suburban neighborhood in the northern part of Mumbai, India, known for its residential complexes, shopping malls, and commercial development.
  • C. Malakula
    Malakula is one of the largest and most culturally diverse islands of Vanuatu, known for its many distinct languages and traditional customs.
  • D. Maléter
    Maléter is the surname of Pál Maléter, a Hungarian military officer and key figure in the 1956 Hungarian Revolution.
  • E. Madadeni
    Madadeni is a township in KwaZulu-Natal, South Africa, situated near Newcastle and known as a large residential and industrial area in the region.
  • 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_69d6ab2945d081908a5851c916cbcfb5 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8be1cad5c8190a45dfb0f0cc2a512 completed April 10, 2026, 9:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69f417cb1c3881909ee50e8d11621664 completed May 1, 2026, 3:02 a.m.
Created at: April 8, 2026, 9:44 p.m.