Triple

T1363020
Position Surface form Disambiguated ID Type / Status
Subject Teide E29138 entity
Predicate isHighestPointOf P210 FINISHED
Object Tenerife E32105 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: Tenerife | Statement: [Teide, isHighestPointOf, Tenerife]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tenerife
Context triple: [Teide, isHighestPointOf, Tenerife]
  • A. Tenerife chosen
    Tenerife is the largest and most populous of Spain’s Canary Islands, renowned for its volcanic landscapes, beaches, and the towering Mount Teide.
  • B. Gran Canaria
    Gran Canaria is a major Spanish island in the Atlantic Ocean known for its diverse landscapes, popular beach resorts, and status as a key tourist destination in the Canary Islands.
  • C. Lanzarote
    Lanzarote is a Spanish volcanic island in the Atlantic Ocean known for its dramatic lava landscapes, year-round mild climate, and status as a popular tourist destination.
  • D. Fuerteventura
    Fuerteventura is a major Canary Island known for its extensive sandy beaches, strong winds ideal for water sports, and arid volcanic landscapes.
  • E. La Gomera
    La Gomera is a small, rugged volcanic island in Spain’s Canary Islands, known for its dramatic ravines, laurel forests, and traditional whistled language, Silbo Gomero.
  • 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_69a498d77abc8190913bf57e5f51d2c4 completed March 1, 2026, 7:51 p.m.
NER Named-entity recognition batch_69a4c2b4ab3c8190ad692e32eee05976 completed March 1, 2026, 10:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad08a7ed5c8190b9f99a6f4524eae8 completed March 8, 2026, 5:27 a.m.
Created at: March 1, 2026, 7:57 p.m.