Triple

T24729334
Position Surface form Disambiguated ID Type / Status
Subject Breton people E618240 entity
Predicate historicalKingdom P20193 FINISHED
Object Kingdom of Brittany
The Kingdom of Brittany was a medieval polity in western France ruled by Breton leaders, known for its distinct Celtic culture and periodic autonomy from Frankish and later French control.
E1647763 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: Kingdom of Brittany | Statement: [Breton people, historicalKingdom, Kingdom of Brittany]
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: Kingdom of Brittany
Triple: [Breton people, historicalKingdom, Kingdom of Brittany]
Generated description
The Kingdom of Brittany was a medieval polity in western France ruled by Breton leaders, known for its distinct Celtic culture and periodic autonomy from Frankish and later French control.

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_69e2fab772608190b74163751047ff50 completed April 18, 2026, 3:29 a.m.
NER Named-entity recognition batch_69f4103505a8819094cc995e8ac34dcf completed May 1, 2026, 2:30 a.m.
NED1 Entity disambiguation (via context triple) batch_6a10101c96fc8190a55c5ce348455541 completed May 22, 2026, 8:13 a.m.
NEDg Description generation batch_6a10136e15dc81908478704742d7c95e completed May 22, 2026, 8:27 a.m.
NED2 Entity disambiguation (via description) batch_6a10145c05c88190a29367197865506c completed May 22, 2026, 8:31 a.m.
Created at: April 18, 2026, 4:01 a.m.