Triple

T38468183
Position Surface form Disambiguated ID Type / Status
Subject Abondance cheese E912631 entity
Predicate madeFromBreed P106562 FINISHED
Object Montbéliarde cattle
Montbéliarde cattle are a French dual-purpose dairy breed from the Franche-Comté region, valued for their high-quality milk used in traditional Alpine cheeses such as Comté and Abondance.
E2272525 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: Montbéliarde cattle | Statement: [Abondance cheese, madeFromBreed, Montbéliarde cattle]
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: Montbéliarde cattle
Triple: [Abondance cheese, madeFromBreed, Montbéliarde cattle]
Generated description
Montbéliarde cattle are a French dual-purpose dairy breed from the Franche-Comté region, valued for their high-quality milk used in traditional Alpine cheeses such as Comté and Abondance.

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_69f76e861d8c81908559031dc66e3c15 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69fcd1fbc0fc8190a0ef4f1ebb215d0d completed May 7, 2026, 5:55 p.m.
NED1 Entity disambiguation (via context triple) batch_6a41d6498f9481909895f9639e32ea76 completed June 29, 2026, 2:19 a.m.
NEDg Description generation batch_6a41d80349a0819094c78793b803ff49 completed June 29, 2026, 2:27 a.m.
NED2 Entity disambiguation (via description) batch_6a41d862098c819090728ec5fe64371d completed June 29, 2026, 2:28 a.m.
Created at: May 3, 2026, 4:31 p.m.