Triple

T24967645

Position	Surface form	Disambiguated ID	Type / Status
Subject	Gruffudd ap Llywelyn	`E624792`	entity
Predicate	mother	`P120`	FINISHED
Object	Angharad ferch Maredudd Angharad ferch Maredudd was a Welsh noblewoman of the 11th century, best known as the mother of Gruffudd ap Llywelyn, the only ruler to unite all of Wales under his kingship.	`E1675185`	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: Angharad ferch Maredudd | Statement: [Gruffudd ap Llywelyn, mother, Angharad ferch Maredudd]

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: Angharad ferch Maredudd
Triple: [Gruffudd ap Llywelyn, mother, Angharad ferch Maredudd]

Generated description

Angharad ferch Maredudd was a Welsh noblewoman of the 11th century, best known as the mother of Gruffudd ap Llywelyn, the only ruler to unite all of Wales under his kingship.

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_69e2ff24512481908e9a72315b8d0354`	completed	April 18, 2026, 3:48 a.m.
NER	Named-entity recognition	`batch_69f444da32748190a155dc92632bb585`	completed	May 1, 2026, 6:14 a.m.
NED1	Entity disambiguation (via context triple)	`batch_6a1075b3dfec8190b6f4ac130c3c0386`	completed	May 22, 2026, 3:26 p.m.
NEDg	Description generation	`batch_6a1076991b208190945d037fd9eef5f2`	completed	May 22, 2026, 3:30 p.m.
NED2	Entity disambiguation (via description)	`batch_6a1077b79abc819099f92e2e2cc19c5d`	completed	May 22, 2026, 3:35 p.m.

Created at: April 18, 2026, 6 a.m.