Triple

T14482321
Position Surface form Disambiguated ID Type / Status
Subject Belvedere glacier viewpoint E359136 entity
Predicate near P350 FINISHED
Object Macugnaga E72900 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: Macugnaga | Statement: [Belvedere glacier viewpoint, near, Macugnaga]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Macugnaga
Context triple: [Belvedere glacier viewpoint, near, Macugnaga]
  • A. Macugnaga chosen
    Macugnaga is a picturesque alpine village in Italy’s Piedmont region, known for its traditional Walser culture and its location at the foot of the Monte Rosa massif.
  • B. Guindulungan
    Guindulungan is a municipality in the province of Maguindanao in the Bangsamoro Autonomous Region in Muslim Mindanao in the southern Philippines.
  • C. Matagot
    Matagot is a French board game publisher known for producing innovative and thematic tabletop games.
  • D. Mambajao
    Mambajao is a coastal municipality in the Philippines known as the main commercial and administrative center of Camiguin Island.
  • E. Cala-agus
    Cala-agus is a barangay (village-level administrative division) of the municipality of Dumalag in the Philippines.
  • 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_69d827966698819082e140837737501d completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de924bc548819087a2f693840d7426 completed April 14, 2026, 7:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69fee5dc9b908190b1d7583810dc9c41 completed May 9, 2026, 7:44 a.m.
Created at: April 10, 2026, 1:20 a.m.