Triple

T37189722
Position Surface form Disambiguated ID Type / Status
Subject Judicael of Brittany E921416 entity
Predicate positionHeld P8 FINISHED
Object King of Domnonée
The King of Domnonée was the ruler of a medieval Breton kingdom in northwestern Armorica, associated with early Breton leaders such as Judicael of Brittany.
E2216788 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: King of Domnonée | Statement: [Judicael of Brittany, positionHeld, King of Domnonée]
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: King of Domnonée
Triple: [Judicael of Brittany, positionHeld, King of Domnonée]
Generated description
The King of Domnonée was the ruler of a medieval Breton kingdom in northwestern Armorica, associated with early Breton leaders such as Judicael of Brittany.

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_69f76ea250bc819083f28d81de25cd0c completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69fb361a9ce0819088c145f704f3f9fd completed May 6, 2026, 12:37 p.m.
NED1 Entity disambiguation (via context triple) batch_6a40361313148190b6a0cf748e0191b3 completed June 27, 2026, 8:44 p.m.
NEDg Description generation batch_6a403692b8c0819080608b791a585931 completed June 27, 2026, 8:46 p.m.
NED2 Entity disambiguation (via description) batch_6a4037016aa881909a72d303ebec4756 completed June 27, 2026, 8:48 p.m.
Created at: May 3, 2026, 4:15 p.m.