Triple
T9168503
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paul Tortelier |
E220024
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Paul Tortelier |
E220024
|
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: Paul Tortelier | Statement: [Paul Tortelier, name, Paul Tortelier]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Paul Tortelier Context triple: [Paul Tortelier, name, Paul Tortelier]
-
A.
Paul Tortelier
chosen
Paul Tortelier was a renowned French cellist and pedagogue celebrated for his expressive performances and influential teaching career.
-
B.
Bruno Coulais
Bruno Coulais is a French composer best known for his atmospheric and innovative film scores, particularly in European cinema and animation.
-
C.
Antoine Predock
Antoine Predock is an American architect renowned for his expressive, landscape-inspired designs, including major cultural and civic projects around the world.
-
D.
Philippe Starck
Philippe Starck is a renowned French designer celebrated for his innovative and often whimsical industrial, interior, and product designs across furniture, architecture, and everyday objects.
-
E.
Philippe Rousselot
Philippe Rousselot is an acclaimed French cinematographer known for his visually distinctive work on numerous major films across several decades.
- 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_69ca83e467108190abcae6a33b3d4dad |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccaadfb50881909b9127f92e4b3e21 |
completed | April 1, 2026, 5:19 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d065cd42f481909ad3c68372041b1a |
completed | April 4, 2026, 1:13 a.m. |
Created at: March 30, 2026, 7:22 p.m.