Triple

T27705142
Position Surface form Disambiguated ID Type / Status
Subject Pierre Mendès France E698532 entity
Predicate notableWork P4 FINISHED
Object La République moderne
La République moderne is a political work by Pierre Mendès France in which he outlines his vision for a reformed, more democratic and socially just French Republic.
E1786306 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: La République moderne | Statement: [Pierre Mendès France, notableWork, La République moderne]
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: La République moderne
Triple: [Pierre Mendès France, notableWork, La République moderne]
Generated description
La République moderne is a political work by Pierre Mendès France in which he outlines his vision for a reformed, more democratic and socially just French Republic.

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_69ef590f655c81909f93893b3b3219b2 completed April 27, 2026, 12:39 p.m.
NER Named-entity recognition batch_69f635a632788190b483e2baff237255 completed May 2, 2026, 5:34 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12e45d4f80819084d10e56eede036c completed May 24, 2026, 11:43 a.m.
NEDg Description generation batch_6a12e4fca4088190b20187243cbf974e completed May 24, 2026, 11:46 a.m.
NED2 Entity disambiguation (via description) batch_6a12e606bc688190958b5e84777566fb completed May 24, 2026, 11:50 a.m.
Created at: April 27, 2026, 2:59 p.m.