Triple

T16617339
Position Surface form Disambiguated ID Type / Status
Subject Limousin Occitan E403727 entity
Predicate hasAlternativeName P39 FINISHED
Object Lemosin
Lemosin is a variety of the Occitan language traditionally spoken in the Limousin region of central France.
 E1223874 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: Lemosin | Statement: [Limousin Occitan, hasAlternativeName, Lemosin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lemosin
Context triple: [Limousin Occitan, hasAlternativeName, Lemosin]
  • A. Perote
    Perote is a municipality and town in the Mexican state of Veracruz, known for its high-altitude location, cold climate, and proximity to the Cofre de Perote volcano.
  • B. Lezo
    Lezo is a small inland municipality in the province of Aklan in the Philippines, known for its rural character and local agricultural economy.
  • C. Lezo
    Lezo is a small town in the Basque Country of northern Spain, located near the Bay of Pasaia in the province of Gipuzkoa.
  • D. Dolo
    Dolo is an Italian stream that serves as a tributary of the Secchia River in northern Italy.
  • E. Dolo
    Dolo is a historic town in northeastern Italy, situated along the Brenta River between Venice and Padua.
  • 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: Lemosin
Triple: [Limousin Occitan, hasAlternativeName, Lemosin]
Generated description
Lemosin is a variety of the Occitan language traditionally spoken in the Limousin region of central France.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lemosin
Target entity description: Lemosin is a variety of the Occitan language traditionally spoken in the Limousin region of central France.
  • A. Perote
    Perote is a municipality and town in the Mexican state of Veracruz, known for its high-altitude location, cold climate, and proximity to the Cofre de Perote volcano.
  • B. Lezo
    Lezo is a small inland municipality in the province of Aklan in the Philippines, known for its rural character and local agricultural economy.
  • C. Lezo
    Lezo is a small town in the Basque Country of northern Spain, located near the Bay of Pasaia in the province of Gipuzkoa.
  • D. Dolo
    Dolo is an Italian stream that serves as a tributary of the Secchia River in northern Italy.
  • E. Dolo
    Dolo is a historic town in northeastern Italy, situated along the Brenta River between Venice and Padua.
  • 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_69d883897eb481909eaaa088ba9918d9 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3754ac9dc8190965197024594742b completed April 18, 2026, 12:12 p.m.
NED1 Entity disambiguation (via context triple) batch_6a007daef18481908c3628a3466300ce completed May 10, 2026, 12:44 p.m.
NEDg Description generation batch_6a007e6507208190b3f32c05a2f647bd completed May 10, 2026, 12:47 p.m.
NED2 Entity disambiguation (via description) batch_6a007f2cefa081908734a907da33a72f completed May 10, 2026, 12:50 p.m.
Created at: April 10, 2026, 5:17 a.m.