Triple

T32276506
Position Surface form Disambiguated ID Type / Status
Subject Ermengarde of Tours E824560 entity
Predicate mother P120 FINISHED
Object Ava of Morvois
Ava of Morvois was a 9th-century Frankish noblewoman associated with the aristocracy of the Carolingian realm, known primarily through her familial ties to prominent regional rulers.
E1999643 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: Ava of Morvois | Statement: [Ermengarde of Tours, mother, Ava of Morvois]
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: Ava of Morvois
Triple: [Ermengarde of Tours, mother, Ava of Morvois]
Generated description
Ava of Morvois was a 9th-century Frankish noblewoman associated with the aristocracy of the Carolingian realm, known primarily through her familial ties to prominent regional rulers.

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_69f3490f404081908450db66884f4334 completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6bcc52ce48190b58a259b036c85b2 completed May 3, 2026, 3:11 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2f46e583dc8190be311b497dd0df04 completed June 15, 2026, 12:27 a.m.
NEDg Description generation batch_6a2f4a190df08190ba2c57645c7785e2 completed June 15, 2026, 12:40 a.m.
NED2 Entity disambiguation (via description) batch_6a2f4a7566248190b0c86d3586545671 completed June 15, 2026, 12:42 a.m.
Created at: May 1, 2026, 12:43 a.m.