Triple

T33207138
Position Surface form Disambiguated ID Type / Status
Subject Pointe de la Sambuy E850042 entity
Predicate category P87 FINISHED
Object Mountains of Haute-Savoie
The Mountains of Haute-Savoie are a group of prominent Alpine peaks in the Haute-Savoie department of southeastern France, known for their dramatic scenery and outdoor recreation.
 E2041385 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: Mountains of Haute-Savoie | Statement: [Pointe de la Sambuy, category, Mountains of Haute-Savoie]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Mountains of Haute-Savoie
Triple: [Pointe de la Sambuy, category, Mountains of Haute-Savoie]
Generated description
The Mountains of Haute-Savoie are a group of prominent Alpine peaks in the Haute-Savoie department of southeastern France, known for their dramatic scenery and outdoor recreation.

Provenance (5 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_69f3495fb92c819083ce65d0ddee7a76 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6da2752b8819084c3a5cf6661f3de completed May 3, 2026, 5:16 a.m.
NED1 Entity disambiguation (via context triple) batch_6a352fc6c310819094904da54c9e7a13 completed June 19, 2026, 12:02 p.m.
NEDg Description generation batch_6a35305f697c8190b02d778d33f27178 completed June 19, 2026, 12:04 p.m.
NED2 Entity disambiguation (via description) batch_6a353242c8148190910123613145e495 completed June 19, 2026, 12:12 p.m.
Created at: May 1, 2026, 1:30 a.m.