Triple

T33073748
Position Surface form Disambiguated ID Type / Status
Subject Marine Le Pen E846304 entity
Predicate sibling P363 FINISHED
Object Marie-Caroline Le Pen
Marie-Caroline Le Pen is a French political figure and member of the Le Pen family, known for her involvement in far-right politics and as the daughter of Jean-Marie Le Pen.
 E2040921 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: Marie-Caroline Le Pen | Statement: [Marine Le Pen, sibling, Marie-Caroline Le Pen]
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: Marie-Caroline Le Pen
Triple: [Marine Le Pen, sibling, Marie-Caroline Le Pen]
Generated description
Marie-Caroline Le Pen is a French political figure and member of the Le Pen family, known for her involvement in far-right politics and as the daughter of Jean-Marie Le Pen.

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_69f3495405b88190967af2157b43b896 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6d3b1123881909714693de00b3789 completed May 3, 2026, 4:48 a.m.
NED1 Entity disambiguation (via context triple) batch_6a352fa8fb0c8190b6a87d714dda65f4 completed June 19, 2026, 12:01 p.m.
NEDg Description generation batch_6a35312477988190b07f6a27ef0cb1a7 completed June 19, 2026, 12:08 p.m.
NED2 Entity disambiguation (via description) batch_6a35317ca8008190b2284c74a1072520 completed June 19, 2026, 12:09 p.m.
Created at: May 1, 2026, 1:25 a.m.