Triple

T16882810
Position Surface form Disambiguated ID Type / Status
Subject Jean Hyppolite E421461 entity
Predicate employer P7 FINISHED
Object Sorbonne NE NERFINISHED

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: Sorbonne | Statement: [Jean Hyppolite, employer, Sorbonne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sorbonne
Context triple: [Jean Hyppolite, employer, Sorbonne]
  • A. La Sorbonne chosen
    La Sorbonne is a historic university building in Paris that has long served as a central symbol of French higher education and intellectual life.
  • B. Sorbon
    Sorbon is a small commune in the Ardennes department of northern France, historically notable as the birthplace of theologian Robert de Sorbon, founder of the Sorbonne.
  • C. Sorbonne University
    Sorbonne University is a major public research university in Paris renowned for its historic humanities, science, and medical faculties.
  • D. Université de Paris
    Université de Paris is a major French public research university in Paris formed through the merger of several former Parisian institutions, known for its broad range of disciplines and strong international profile.
  • E. Sorbonne Nouvelle University
    Sorbonne Nouvelle University is a Paris-based public university renowned for its programs in languages, literature, arts, and humanities, continuing the academic legacy of the historic Sorbonne.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d889d470fc8190b4aec199636c0c56 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e3bbbdffd8819093f1efd91f6d49dc completed April 18, 2026, 5:13 p.m.
Created at: April 10, 2026, 5:29 a.m.