Triple

T30865132
Position Surface form Disambiguated ID Type / Status
Subject Pierre et Jean E786176 entity
Predicate mainCharacter P1183 FINISHED
Object Jean Roland
Jean Roland is one of the two central brothers whose strained relationship and questions of inheritance drive the psychological drama in Guy de Maupassant’s novel "Pierre et Jean."
E2147591 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: Jean Roland | Statement: [Pierre et Jean, mainCharacter, Jean Roland]
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: Jean Roland
Triple: [Pierre et Jean, mainCharacter, Jean Roland]
Generated description
Jean Roland is one of the two central brothers whose strained relationship and questions of inheritance drive the psychological drama in Guy de Maupassant’s novel "Pierre et Jean."

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_69f224b9df2c819086f55f8bcf7f382e completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f691ac00448190b6b89a8c4cb0c9c0 completed May 3, 2026, 12:07 a.m.
NED1 Entity disambiguation (via context triple) batch_6a385bb22d0c8190a2fbb1d8f570d805 completed June 21, 2026, 9:46 p.m.
NEDg Description generation batch_6a385cfee66c8190a546393089b8d789 completed June 21, 2026, 9:51 p.m.
NED2 Entity disambiguation (via description) batch_6a385df5220881908ae1a6c6e999e3fa completed June 21, 2026, 9:56 p.m.
Created at: April 29, 2026, 8:47 p.m.