Triple

T38259367
Position Surface form Disambiguated ID Type / Status
Subject Modeste Mignon E1017884 entity
Predicate basedOn P98 FINISHED
Object Modeste Mignon (novel)
Modeste Mignon is an 1844 novel by Honoré de Balzac that follows the emotional and social awakening of a young Norman woman who tests the sincerity of men through a literary correspondence.
E2262348 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: Modeste Mignon (novel) | Statement: [Modeste Mignon, basedOn, Modeste Mignon (novel)]
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: Modeste Mignon (novel)
Triple: [Modeste Mignon, basedOn, Modeste Mignon (novel)]
Generated description
Modeste Mignon is an 1844 novel by Honoré de Balzac that follows the emotional and social awakening of a young Norman woman who tests the sincerity of men through a literary correspondence.

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_69f76de33e4481909099fa812709bd42 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69fcb1bd17e48190ad3f4f2c3793f084 completed May 7, 2026, 3:37 p.m.
NED1 Entity disambiguation (via context triple) batch_6a4193d2caf08190af475b269ee6e333 completed June 28, 2026, 9:36 p.m.
NEDg Description generation batch_6a419490d3048190aef9f21f06582c91 completed June 28, 2026, 9:39 p.m.
NED2 Entity disambiguation (via description) batch_6a419547a7fc8190a57a5b1d77442730 completed June 28, 2026, 9:42 p.m.
Created at: May 3, 2026, 4:30 p.m.