Triple

T28259999
Position Surface form Disambiguated ID Type / Status
Subject Dialogues des Carmélites E712557 entity
Predicate character P662 FINISHED
Object Madame de Croissy
Madame de Croissy is the dying prioress of the Carmelite convent in Francis Poulenc’s opera "Dialogues des Carmélites," whose harrowing death scene profoundly shapes the spiritual journey of the other nuns.
 E1810063 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: Madame de Croissy | Statement: [Dialogues des Carmélites, character, Madame de Croissy]
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: Madame de Croissy
Triple: [Dialogues des Carmélites, character, Madame de Croissy]
Generated description
Madame de Croissy is the dying prioress of the Carmelite convent in Francis Poulenc’s opera "Dialogues des Carmélites," whose harrowing death scene profoundly shapes the spiritual journey of the other nuns.

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_69efb5207eb08190827e4c34048030b1 completed April 27, 2026, 7:12 p.m.
NER Named-entity recognition batch_69f64417c3f081908eb1950a94b7be65 completed May 2, 2026, 6:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1607151a688190afb8d86db54e047a completed May 26, 2026, 8:48 p.m.
NEDg Description generation batch_6a160cb5d4b0819088ff87a690ce06ba completed May 26, 2026, 9:12 p.m.
NED2 Entity disambiguation (via description) batch_6a160d55a0148190bbec8e5bdac907fd completed May 26, 2026, 9:15 p.m.
Created at: April 27, 2026, 11:11 p.m.