Triple

T26217960
Position Surface form Disambiguated ID Type / Status
Subject Catherine of Foix E655680 entity
Predicate child P120 FINISHED
Object Madeleine of Navarre
Madeleine of Navarre was a 15th–16th century French princess of the House of Foix who became Queen consort of Navarre through her marriage to King John II of Aragon and Navarre.
E1794369 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: Madeleine of Navarre | Statement: [Catherine of Foix, child, Madeleine of Navarre]
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: Madeleine of Navarre
Triple: [Catherine of Foix, child, Madeleine of Navarre]
Generated description
Madeleine of Navarre was a 15th–16th century French princess of the House of Foix who became Queen consort of Navarre through her marriage to King John II of Aragon and Navarre.

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_69ee5b4a77e08190bfcb5f8ecdc55abd completed April 26, 2026, 6:36 p.m.
NER Named-entity recognition batch_69f60d1cd19081909f7575479d6b91ca completed May 2, 2026, 2:41 p.m.
NED1 Entity disambiguation (via context triple) batch_6a13031d018081909235882ebde7e850 completed May 24, 2026, 1:54 p.m.
NEDg Description generation batch_6a13041668688190ae7b83c139db490d completed May 24, 2026, 1:58 p.m.
NED2 Entity disambiguation (via description) batch_6a130608e7648190b7666813a297e308 completed May 24, 2026, 2:07 p.m.
Created at: April 26, 2026, 8:55 p.m.