Triple

T24817216
Position Surface form Disambiguated ID Type / Status
Subject Owain Gwynedd E620956 entity
Predicate child P120 FINISHED
Object Maelgwn ab Owain Gwynedd
Maelgwn ab Owain Gwynedd was a 12th-century Welsh prince, one of the sons of King Owain Gwynedd, who played a role in the turbulent dynastic struggles of medieval Gwynedd.
 E1787806 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: Maelgwn ab Owain Gwynedd | Statement: [Owain Gwynedd, child, Maelgwn ab Owain Gwynedd]
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: Maelgwn ab Owain Gwynedd
Triple: [Owain Gwynedd, child, Maelgwn ab Owain Gwynedd]
Generated description
Maelgwn ab Owain Gwynedd was a 12th-century Welsh prince, one of the sons of King Owain Gwynedd, who played a role in the turbulent dynastic struggles of medieval Gwynedd.

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_69e2fabfd4648190bd0e5c7f4dbb6cab completed April 18, 2026, 3:30 a.m.
NER Named-entity recognition batch_69f4229401148190ab5b57da94aea80d completed May 1, 2026, 3:48 a.m.
NED1 Entity disambiguation (via context triple) batch_6a12ec8329f08190b6b41160368b7a44 completed May 24, 2026, 12:18 p.m.
NEDg Description generation batch_6a12ed2afa9481909cc0ca56270ba2a0 completed May 24, 2026, 12:20 p.m.
NED2 Entity disambiguation (via description) batch_6a12edccfe54819094da363072bdf7a6 completed May 24, 2026, 12:23 p.m.
Created at: April 18, 2026, 5:03 a.m.