Triple

T17087766
Position Surface form Disambiguated ID Type / Status
Subject Lousã E414642 entity
Predicate hasViewpoint P854 FINISHED
Object Alto de Trevim E1166852 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: Alto de Trevim | Statement: [Lousã, hasViewpoint, Alto de Trevim]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alto de Trevim
Context triple: [Lousã, hasViewpoint, Alto de Trevim]
  • A. Alto de Trevim chosen
    Alto de Trevim is a prominent mountain peak and scenic viewpoint in Portugal’s Serra da Lousã range, known for its expansive panoramic views over the surrounding landscape.
  • B. Monte d’Oro
    Monte d’Oro is a prominent mountain peak in central Corsica, known for its rugged terrain and panoramic views over the island’s interior.
  • C. Hoëgne
    Hoëgne is a river in eastern Belgium that flows through the Ardennes region before joining the Vesdre.
  • D. Mauvezin
    Mauvezin is a small commune in southwestern France, located in the Gers department within the Occitanie region.
  • E. Monteiasi
    Monteiasi is a small town and comune in the Apulia region of southern Italy, known for its traditional rural character and proximity to the city of Taranto.
  • 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_69d886cef44c8190ba56c44b4e863e64 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3dbe92e488190b947287a968086d5 completed April 18, 2026, 7:30 p.m.
NED1 Entity disambiguation (via context triple) batch_6a012ee81fd08190a7e1f5958fbe3b97 completed May 11, 2026, 1:20 a.m.
Created at: April 10, 2026, 5:35 a.m.