Triple

T24817212
Position Surface form Disambiguated ID Type / Status
Subject Owain Gwynedd E620956 entity
Predicate child P120 FINISHED
Object Hywel ab Owain Gwynedd
Hywel ab Owain Gwynedd was a 12th-century Welsh prince and notable poet, remembered both for his role in the politics of Gwynedd and for his contributions to early Welsh literature.
E1780543 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: Hywel ab Owain Gwynedd | Statement: [Owain Gwynedd, child, Hywel 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: Hywel ab Owain Gwynedd
Triple: [Owain Gwynedd, child, Hywel ab Owain Gwynedd]
Generated description
Hywel ab Owain Gwynedd was a 12th-century Welsh prince and notable poet, remembered both for his role in the politics of Gwynedd and for his contributions to early Welsh literature.

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_6a12d0a457bc8190b2c8354964c26737 completed May 24, 2026, 10:19 a.m.
NEDg Description generation batch_6a12d18a985c819080daa18aa946feaa completed May 24, 2026, 10:23 a.m.
NED2 Entity disambiguation (via description) batch_6a12d28db59c8190a9141f9e352f19b4 completed May 24, 2026, 10:27 a.m.
Created at: April 18, 2026, 5:03 a.m.