Triple

T32161121
Position Surface form Disambiguated ID Type / Status
Subject Gerberga of Burgundy E821428 entity
Predicate child P120 FINISHED
Object William II of Provence
William II of Provence was an early 11th-century Count of Provence known for consolidating regional power in southern France and participating in the politics of the Burgundian and Holy Roman Empires.
 E1998679 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: William II of Provence | Statement: [Gerberga of Burgundy, child, William II of Provence]
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: William II of Provence
Triple: [Gerberga of Burgundy, child, William II of Provence]
Generated description
William II of Provence was an early 11th-century Count of Provence known for consolidating regional power in southern France and participating in the politics of the Burgundian and Holy Roman Empires.

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_69f34905e098819082191a6922a6d607 completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6ba1a2d4c8190aa73a7b9b37c7c0d completed May 3, 2026, 2:59 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2f46c0871881908373cb7794f55604 completed June 15, 2026, 12:26 a.m.
NEDg Description generation batch_6a2f4759204c8190903a9b022f3e4816 completed June 15, 2026, 12:29 a.m.
NED2 Entity disambiguation (via description) batch_6a2f48435cac8190ae6b9801098e7391 completed June 15, 2026, 12:33 a.m.
Created at: May 1, 2026, 12:32 a.m.