Triple

T25183768
Position Surface form Disambiguated ID Type / Status
Subject Chantal Thomas E630657 entity
Predicate educatedAt P5 FINISHED
Object Université Paris-Sorbonne (Paris IV)
Université Paris-Sorbonne (Paris IV) was a leading French humanities and social sciences university in Paris, renowned for its programs in literature, languages, history, and philosophy.
 E1739959 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: Université Paris-Sorbonne (Paris IV) | Statement: [Chantal Thomas, educatedAt, Université Paris-Sorbonne (Paris IV)]
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: Université Paris-Sorbonne (Paris IV)
Triple: [Chantal Thomas, educatedAt, Université Paris-Sorbonne (Paris IV)]
Generated description
Université Paris-Sorbonne (Paris IV) was a leading French humanities and social sciences university in Paris, renowned for its programs in literature, languages, history, and philosophy.

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_69e75a88fdf081908e47ae6e195c14e1 completed April 21, 2026, 11:07 a.m.
NER Named-entity recognition batch_69f46dc920e88190874a516646bf4ff5 completed May 1, 2026, 9:09 a.m.
NED1 Entity disambiguation (via context triple) batch_6a12090e548c81909177040e13c3f300 completed May 23, 2026, 8:07 p.m.
NEDg Description generation batch_6a120a2acf54819094d2f16637877bb7 completed May 23, 2026, 8:12 p.m.
NED2 Entity disambiguation (via description) batch_6a120b0abaf8819087003d4c7978853f completed May 23, 2026, 8:16 p.m.
Created at: April 21, 2026, 12:36 p.m.