Triple

T4041402
Position Surface form Disambiguated ID Type / Status
Subject Toulon E83956 entity
Predicate demonym P191 FINISHED
Object Toulonnais
Toulonnais is the French term for a person or thing originating from the Mediterranean port city of Toulon in southeastern France.
 E408924 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: Toulonnais | Statement: [Toulon, demonym, Toulonnais]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Toulonnais
Context triple: [Toulon, demonym, Toulonnais]
  • A. Louvois
    Louvois was a powerful French statesman, best known as Louis XIV’s influential war minister who significantly shaped France’s military administration in the late 17th century.
  • B. Jougne
    Jougne is a small French commune in the Doubs department of the Bourgogne-Franche-Comté region, known for its location near the Swiss border in the Jura Mountains.
  • C. Larche
    Larche is a small village in the French Alps near the Italian border, known as a gateway to the surrounding mountain passes and hiking routes.
  • D. Louletano
    Louletano is the Portuguese demonym used to refer to people or things originating from the city of Loulé in the Algarve region.
  • E. Sousel
    Sousel is a municipality in Portugal’s Alentejo region, known for its rural landscape, agricultural activities, and traditional whitewashed architecture.
  • 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: Toulonnais
Triple: [Toulon, demonym, Toulonnais]
Generated description
Toulonnais is the French term for a person or thing originating from the Mediterranean port city of Toulon in southeastern France.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Toulonnais
Target entity description: Toulonnais is the French term for a person or thing originating from the Mediterranean port city of Toulon in southeastern France.
  • A. Louvois
    Louvois was a powerful French statesman, best known as Louis XIV’s influential war minister who significantly shaped France’s military administration in the late 17th century.
  • B. Jougne
    Jougne is a small French commune in the Doubs department of the Bourgogne-Franche-Comté region, known for its location near the Swiss border in the Jura Mountains.
  • C. Larche
    Larche is a small village in the French Alps near the Italian border, known as a gateway to the surrounding mountain passes and hiking routes.
  • D. Louletano
    Louletano is the Portuguese demonym used to refer to people or things originating from the city of Loulé in the Algarve region.
  • E. Sousel
    Sousel is a municipality in Portugal’s Alentejo region, known for its rural landscape, agricultural activities, and traditional whitewashed architecture.
  • 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_69aed92f7cf0819098e0539bdcc3767f completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefb3a9314819095dcf47675eedb48 completed March 9, 2026, 4:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69b55649b75c819086b272f56ac73be4 completed March 14, 2026, 12:36 p.m.
NEDg Description generation batch_69b55a1974348190b6c8ca74fb9da47e completed March 14, 2026, 12:52 p.m.
NED2 Entity disambiguation (via description) batch_69b55a828d7881908e3e9a14bc77103c completed March 14, 2026, 12:54 p.m.
Created at: March 9, 2026, 3:37 p.m.