Triple

T14314391
Position Surface form Disambiguated ID Type / Status
Subject Majadahonda E354915 entity
Predicate hasPark P105 FINISHED
Object Monte del Pilar E412310 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: Monte del Pilar | Statement: [Majadahonda, hasPark, Monte del Pilar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Monte del Pilar
Context triple: [Majadahonda, hasPark, Monte del Pilar]
  • A. Monte del Pilar chosen
    Monte del Pilar is a large natural park and green area in Majadahonda, Spain, known for its Mediterranean woodland, walking trails, and recreational spaces.
  • B. Monte Igueldo
    Monte Igueldo is a scenic coastal mountain in San Sebastián, Spain, known for its historic funicular, amusement park, and panoramic views over La Concha Bay.
  • C. Monte de El Pardo
    Monte de El Pardo is a large protected forested area and royal hunting estate on the outskirts of Madrid, Spain, known for its Mediterranean woodland and rich wildlife.
  • D. Monte Rey
    Monte Rey is an otter character known by the shortened name "Monte Rey."
  • E. Monte Toro
    Monte Toro is the tallest mountain on the Spanish island of Menorca, known for its panoramic views and a sanctuary at its summit.
  • 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_69d8278ed42c8190b9f882dcce611347 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de85b49e5481909b9ffab2d922e284 completed April 14, 2026, 6:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd4687c6bc819088452892128c420e completed May 8, 2026, 2:12 a.m.
Created at: April 10, 2026, 1:12 a.m.