Triple

T24377922
Position Surface form Disambiguated ID Type / Status
Subject King Conrad of Burgundy E614528 entity
Predicate spouse P13 FINISHED
Object Adelaide of Bellay
Adelaide of Bellay was a medieval noblewoman known primarily as the wife of King Conrad of Burgundy.
E1735240 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: Adelaide of Bellay | Statement: [King Conrad of Burgundy, spouse, Adelaide of Bellay]
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: Adelaide of Bellay
Triple: [King Conrad of Burgundy, spouse, Adelaide of Bellay]
Generated description
Adelaide of Bellay was a medieval noblewoman known primarily as the wife of King Conrad of Burgundy.

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_69e2d7e362e481909e32fe4ef8269d4f completed April 18, 2026, 1:01 a.m.
NER Named-entity recognition batch_69f293d96e7c8190b2f33a8fd12c32c6 completed April 29, 2026, 11:27 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11ebe4801c8190a22526d402b01e5d completed May 23, 2026, 6:03 p.m.
NEDg Description generation batch_6a11ee266f008190843eb2ee53a4c734 completed May 23, 2026, 6:12 p.m.
NED2 Entity disambiguation (via description) batch_6a11ee9c89dc8190aaa61318e8210888 completed May 23, 2026, 6:14 p.m.
Created at: April 18, 2026, 2:02 a.m.