Triple

T31691581
Position Surface form Disambiguated ID Type / Status
Subject Saint Zélie Martin E808803 entity
Predicate child P120 FINISHED
Object Marie Léonie Martin
Marie Léonie Martin was one of the daughters of Saints Louis and Zélie Martin and the elder sister of Saint Thérèse of Lisieux, who became a Visitation nun known as Sister Françoise-Thérèse.
E1999682 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: Marie Léonie Martin | Statement: [Saint Zélie Martin, child, Marie Léonie Martin]
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: Marie Léonie Martin
Triple: [Saint Zélie Martin, child, Marie Léonie Martin]
Generated description
Marie Léonie Martin was one of the daughters of Saints Louis and Zélie Martin and the elder sister of Saint Thérèse of Lisieux, who became a Visitation nun known as Sister Françoise-Thérèse.

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_69f348ddcbc48190950cabcc25ff29b3 completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f6aa821a608190903bbbb8cd64f79e completed May 3, 2026, 1:53 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2f46b1602c8190a7cd3a59c380e59c completed June 15, 2026, 12:26 a.m.
NEDg Description generation batch_6a2f4aa3d64481908a3252f02d4c752a completed June 15, 2026, 12:43 a.m.
NED2 Entity disambiguation (via description) batch_6a2f4aff2aa48190984dcbf5f3bffd86 completed June 15, 2026, 12:44 a.m.
Created at: April 30, 2026, 11:08 p.m.