Triple

T26217963
Position Surface form Disambiguated ID Type / Status
Subject Catherine of Foix E655680 entity
Predicate child P120 FINISHED
Object Andrew of Navarre
Andrew of Navarre was an infante (prince) of the Kingdom of Navarre from the House of Foix-Grailly, notable primarily as a younger son in the Navarrese royal family during the late 15th century.
E1737532 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: Andrew of Navarre | Statement: [Catherine of Foix, child, Andrew 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: Andrew of Navarre
Triple: [Catherine of Foix, child, Andrew of Navarre]
Generated description
Andrew of Navarre was an infante (prince) of the Kingdom of Navarre from the House of Foix-Grailly, notable primarily as a younger son in the Navarrese royal family during the late 15th century.

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_6a11fe4be9448190ba97735f4703678b completed May 23, 2026, 7:21 p.m.
NEDg Description generation batch_6a11ff2e71988190ad6d34bc5420c9bd completed May 23, 2026, 7:25 p.m.
NED2 Entity disambiguation (via description) batch_6a11ffe6aad4819096be2e81c2f3d1b0 completed May 23, 2026, 7:28 p.m.
Created at: April 26, 2026, 8:55 p.m.