Triple

T36866377
Position Surface form Disambiguated ID Type / Status
Subject Simon IV de Montfort E911093 entity
Predicate child P120 FINISHED
Object Laudina de Montfort
Laudina de Montfort was a lesser-known medieval noblewoman of the influential Montfort family, born to the French noble and crusader Simon IV de Montfort.
E2206343 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: Laudina de Montfort | Statement: [Simon IV de Montfort, child, Laudina de Montfort]
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: Laudina de Montfort
Triple: [Simon IV de Montfort, child, Laudina de Montfort]
Generated description
Laudina de Montfort was a lesser-known medieval noblewoman of the influential Montfort family, born to the French noble and crusader Simon IV de Montfort.

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_69f76e80f6f0819091cba8e19b269615 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69f7cfd48dc48190885f1ead97d4ce46 completed May 3, 2026, 10:44 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3e2c2496e88190ba56462dcde53d88 completed June 26, 2026, 7:37 a.m.
NEDg Description generation batch_6a3e2cf5b99c8190b0f2573e57f9d5d7 completed June 26, 2026, 7:40 a.m.
NED2 Entity disambiguation (via description) batch_6a3e43348bd88190bd7b9886e07e2a65 completed June 26, 2026, 9:15 a.m.
Created at: May 3, 2026, 4:13 p.m.