Triple

T26410780
Position Surface form Disambiguated ID Type / Status
Subject Lords of Coucy E663952 entity
Predicate foundedBy P104 FINISHED
Object Aubry de Coucy
Aubry de Coucy was a medieval French nobleman recognized as the progenitor of the influential Lords of Coucy lineage.
E1728564 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: Aubry de Coucy | Statement: [Lords of Coucy, foundedBy, Aubry de Coucy]
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: Aubry de Coucy
Triple: [Lords of Coucy, foundedBy, Aubry de Coucy]
Generated description
Aubry de Coucy was a medieval French nobleman recognized as the progenitor of the influential Lords of Coucy lineage.

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_69ee883931888190901be96d75ee23cc completed April 26, 2026, 9:48 p.m.
NER Named-entity recognition batch_69f6113143f481909c64dfc1975e3a59 completed May 2, 2026, 2:58 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11bb10a3c081908895c846894ea743 completed May 23, 2026, 2:34 p.m.
NEDg Description generation batch_6a11be5f621881908d83370dd283a10f completed May 23, 2026, 2:49 p.m.
NED2 Entity disambiguation (via description) batch_6a11bf7e1de48190ba8ed044628d5bf7 completed May 23, 2026, 2:53 p.m.
Created at: April 26, 2026, 11:37 p.m.