Triple

T14059456
Position Surface form Disambiguated ID Type / Status
Subject Louise Bourgeois E338305 entity
Predicate educatedAt P5 FINISHED
Object Sorbonne E16381 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: Sorbonne | Statement: [Louise Bourgeois, educatedAt, Sorbonne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sorbonne
Context triple: [Louise Bourgeois, educatedAt, 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. 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.
  • E. Panthéon-Sorbonne University
    Panthéon-Sorbonne University is a prestigious Parisian institution renowned for its programs in law, humanities, and social sciences, and its historical roots in the University of Paris.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d81c67ba6c819091935650dfb3b895 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de5686f51c81908c33143ecbaae83d completed April 14, 2026, 3 p.m.
NED1 Entity disambiguation (via context triple) batch_69fff288ba908190a36c4784331d1e60 completed May 10, 2026, 2:50 a.m.
Created at: April 9, 2026, 10:21 p.m.