Triple

T32406742
Position Surface form Disambiguated ID Type / Status
Subject I Promessi Sposi E828103 entity
Predicate character P662 FINISHED
Object Fra Cristoforo
Fra Cristoforo is a courageous and compassionate Capuchin friar in Alessandro Manzoni’s novel "I Promessi Sposi," known for defending the oppressed and seeking justice.
E783722 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: Fra Cristoforo | Statement: [I Promessi Sposi, character, Fra Cristoforo]
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: Fra Cristoforo
Triple: [I Promessi Sposi, character, Fra Cristoforo]
Generated description
Fra Cristoforo is a courageous and compassionate Capuchin friar in Alessandro Manzoni’s novel "I Promessi Sposi," known for defending the oppressed and seeking justice.

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_69f34919342c8190a4c3bf35a90d4e58 completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6c247928481908f5aa369adfd2906 completed May 3, 2026, 3:34 a.m.
NED1 Entity disambiguation (via context triple) batch_6a344f19d5148190824eaf0a09d4f2fd completed June 18, 2026, 8:03 p.m.
NEDg Description generation batch_6a345027c89881908d7b232b5d6f2a1d completed June 18, 2026, 8:08 p.m.
NED2 Entity disambiguation (via description) batch_6a345b74cec48190a846e0d129ea4c07 completed June 18, 2026, 8:56 p.m.
Created at: May 1, 2026, 12:53 a.m.