Triple

T6671474
Position Surface form Disambiguated ID Type / Status
Subject Mont Ventoux E151739 entity
Predicate nearbyTown P3883 FINISHED
Object Malaucène
Malaucène is a picturesque Provençal village in southeastern France, known as a popular base for cyclists and tourists visiting and climbing Mont Ventoux.
 E618876 NE FINISHED

How this triple was built (4 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: Malaucène | Statement: [Mont Ventoux, nearbyTown, Malaucène]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Malaucène
Context triple: [Mont Ventoux, nearbyTown, Malaucène]
  • A. Mouriès
    Mouriès is a village in southern France’s Provence region, known for its olive oil production and location near the Alpilles hills.
  • B. Vauvert
    Vauvert is a commune in southern France known for its location in the Gard department near the Camargue region.
  • C. Peseux
    Peseux is a former municipality in the canton of Neuchâtel in western Switzerland, now part of the city of Neuchâtel.
  • D. Lezoux
    Lezoux is a commune in central France’s Puy-de-Dôme department, known historically for its significant Roman pottery production.
  • E. Vallauris
    Vallauris is a town in the French Riviera renowned for its pottery tradition and its association with Pablo Picasso, who lived and worked there for several years.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Malaucène
Triple: [Mont Ventoux, nearbyTown, Malaucène]
Generated description
Malaucène is a picturesque Provençal village in southeastern France, known as a popular base for cyclists and tourists visiting and climbing Mont Ventoux.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Malaucène
Target entity description: Malaucène is a picturesque Provençal village in southeastern France, known as a popular base for cyclists and tourists visiting and climbing Mont Ventoux.
  • A. Mouriès
    Mouriès is a village in southern France’s Provence region, known for its olive oil production and location near the Alpilles hills.
  • B. Vauvert
    Vauvert is a commune in southern France known for its location in the Gard department near the Camargue region.
  • C. Peseux
    Peseux is a former municipality in the canton of Neuchâtel in western Switzerland, now part of the city of Neuchâtel.
  • D. Lezoux
    Lezoux is a commune in central France’s Puy-de-Dôme department, known historically for its significant Roman pottery production.
  • E. Vallauris
    Vallauris is a town in the French Riviera renowned for its pottery tradition and its association with Pablo Picasso, who lived and worked there for several years.
  • F. None of above. chosen

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_69c687f71fc081909dbd45d6377f6045 completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6b0ca49f88190b9c8e0f641be0c3f completed March 27, 2026, 4:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69c71a67cae081908f61e5bc0cafcd2b completed March 28, 2026, 12:01 a.m.
NEDg Description generation batch_69c71b186238819096ef6162f9068543 completed March 28, 2026, 12:04 a.m.
NED2 Entity disambiguation (via description) batch_69c71b98b8008190a972cc0a215295c0 completed March 28, 2026, 12:06 a.m.
Created at: March 27, 2026, 2:03 p.m.