Triple

T31608550
Position Surface form Disambiguated ID Type / Status
Subject Saint Louis Martin E806560 entity
Predicate child P120 FINISHED
Object Marie Mélanie-Thérèse
Marie Mélanie-Thérèse was one of the lesser-known daughters in the devout Catholic family of Saint Louis Martin, the father of Saint Thérèse of Lisieux.
E1973975 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 Mélanie-Thérèse | Statement: [Saint Louis Martin, child, Marie Mélanie-Thérèse]
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 Mélanie-Thérèse
Triple: [Saint Louis Martin, child, Marie Mélanie-Thérèse]
Generated description
Marie Mélanie-Thérèse was one of the lesser-known daughters in the devout Catholic family of Saint Louis Martin, the father of Saint Thérèse of Lisieux.

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_69f348d61f2081908cad94bc9ffbb671 completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f6a87155008190a0e37892fce005eb completed May 3, 2026, 1:44 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2b84a608fc81909169a71d1c51a42f completed June 12, 2026, 4:01 a.m.
NEDg Description generation batch_6a2b857dd8708190984e04b26d63e120 completed June 12, 2026, 4:05 a.m.
NED2 Entity disambiguation (via description) batch_6a2b8680bf2481908a1d59faf84ade89 completed June 12, 2026, 4:09 a.m.
Created at: April 30, 2026, 10:35 p.m.