Triple

T16140280
Position Surface form Disambiguated ID Type / Status
Subject GR 20 E391634 entity
Predicate startPoint P389 FINISHED
Object Calenzana E391636 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: Calenzana | Statement: [GR 20, startPoint, Calenzana]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Calenzana
Context triple: [GR 20, startPoint, Calenzana]
  • A. Calenzana chosen
    Calenzana is a village in the Haute-Corse department of Corsica, France, known as a gateway to the island’s mountainous interior and a starting point for hiking and outdoor tourism.
  • B. Sinalunga
    Sinalunga is a historic town in Tuscany, central Italy, known for its medieval architecture and scenic location within the rolling hills of the Val di Chiana.
  • C. Casciana Terme Lari
    Casciana Terme Lari is a municipality in Tuscany, central Italy, known for its historic hilltop village of Lari and the thermal spa resort of Casciana Terme.
  • D. Rosciano
    Rosciano is a small Italian municipality in the Abruzzo region, known for its rural landscape and traditional local agriculture.
  • E. Monterchi
    Monterchi is a small Tuscan hill town in central Italy, renowned for its picturesque medieval setting and Piero della Francesca’s famous fresco "Madonna del Parto."
  • 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_69d87f1bb0988190b490d273dbf3fd03 completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e21a07b7908190b4e1ec57f60a9274 completed April 17, 2026, 11:31 a.m.
NED1 Entity disambiguation (via context triple) batch_69fff2b75988819094baaff8f53f48ce completed May 10, 2026, 2:51 a.m.
Created at: April 10, 2026, 5:01 a.m.