Triple

T26327813
Position Surface form Disambiguated ID Type / Status
Subject King of Deheubarth E662302 entity
Predicate hasTitleHolder P1911 FINISHED
Object Anarawd ap Rhys
Anarawd ap Rhys was a medieval Welsh prince who ruled the kingdom of Deheubarth in southwest Wales.
E1862067 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: Anarawd ap Rhys | Statement: [King of Deheubarth, hasTitleHolder, Anarawd ap Rhys]
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: Anarawd ap Rhys
Triple: [King of Deheubarth, hasTitleHolder, Anarawd ap Rhys]
Generated description
Anarawd ap Rhys was a medieval Welsh prince who ruled the kingdom of Deheubarth in southwest Wales.

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_69ee812f32748190871d970c4e2a8ddf completed April 26, 2026, 9:18 p.m.
NER Named-entity recognition batch_69f60f65f9f48190ba299fb3e435e67a completed May 2, 2026, 2:51 p.m.
NED1 Entity disambiguation (via context triple) batch_6a25a82c50508190adc6b7453185b9c4 completed June 7, 2026, 5:19 p.m.
NEDg Description generation batch_6a25ac6034a081909518662153fbe1b3 completed June 7, 2026, 5:37 p.m.
NED2 Entity disambiguation (via description) batch_6a25b13620148190ab87852c2312d21f completed June 7, 2026, 5:58 p.m.
Created at: April 26, 2026, 10:32 p.m.