Triple

T11629291
Position Surface form Disambiguated ID Type / Status
Subject Vignemale massif E276352 entity
Predicate viewedFrom P9787 FINISHED
Object Lac de Gaube E428689 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: Lac de Gaube | Statement: [Vignemale massif, viewedFrom, Lac de Gaube]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lac de Gaube
Context triple: [Vignemale massif, viewedFrom, Lac de Gaube]
  • A. Lac de Gaube chosen
    Lac de Gaube is a scenic glacial lake in the French Pyrenees, renowned for its turquoise waters and dramatic mountain surroundings near the Vignemale massif.
  • B. Lac de Guéry
    Lac de Guéry is a high-altitude volcanic lake in France’s Massif Central, renowned for its scenic mountain setting and traditional ice fishing.
  • C. Lac de Pannecière
    Lac de Pannecière is a large artificial reservoir in the Morvan region of central France, known for its scenic landscapes, outdoor recreation, and role in regulating the Yonne River.
  • D. Lac de Pareloup
    Lac de Pareloup is a large artificial reservoir in southern France renowned for water sports, fishing, and lakeside tourism.
  • E. Lac de Gravelle
    Lac de Gravelle is a small artificial lake in Paris’s Bois de Vincennes, known for its tranquil setting, walking paths, and role as a recreational green space for city residents.
  • 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_69d6aafa51148190ab84940694c00235 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a127b2688190ae3a340f851e834b completed April 10, 2026, 7:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69f6af38e3548190a5192894932d9b1d completed May 3, 2026, 2:13 a.m.
Created at: April 8, 2026, 9:39 p.m.