Triple

T22547890
Position Surface form Disambiguated ID Type / Status
Subject James II of Bourbon-La Marche E557478 entity
Predicate mother P120 FINISHED
Object Catherine of Vendôme
Catherine of Vendôme was a French noblewoman and Countess of Vendôme from the House of Montoire, notable as an heiress whose lands later passed into the Bourbon family.
E1667326 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: Catherine of Vendôme | Statement: [James II of Bourbon-La Marche, mother, Catherine of Vendôme]
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: Catherine of Vendôme
Triple: [James II of Bourbon-La Marche, mother, Catherine of Vendôme]
Generated description
Catherine of Vendôme was a French noblewoman and Countess of Vendôme from the House of Montoire, notable as an heiress whose lands later passed into the Bourbon family.

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_69e11e58662081909ae346ab384514ca completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15f372df48190ae5dd461b1230bc7 completed April 29, 2026, 1:30 a.m.
NED1 Entity disambiguation (via context triple) batch_6a105ca8a5248190a6f30bfab3aaec80 completed May 22, 2026, 1:39 p.m.
NEDg Description generation batch_6a105e52d9fc8190b22dd25b9cec720b completed May 22, 2026, 1:46 p.m.
NED2 Entity disambiguation (via description) batch_6a105ef626c08190933088d575b2e923 completed May 22, 2026, 1:49 p.m.
Created at: April 16, 2026, 8:52 p.m.