Triple
T7741523
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Étienne Dolet |
E175520
|
entity |
| Predicate | studentOf |
P48
|
FINISHED |
| Object |
Nicolas Bérauld
Nicolas Bérauld was a French Renaissance humanist scholar and teacher known for mentoring figures such as the printer and humanist Étienne Dolet.
|
E691623
|
NE FINISHED |
How this triple was built (4 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: Nicolas Bérauld | Statement: [Étienne Dolet, studentOf, Nicolas Bérauld]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nicolas Bérauld Context triple: [Étienne Dolet, studentOf, Nicolas Bérauld]
-
A.
Nicolas Dufourcq
Nicolas Dufourcq is a French business executive known for leading major technology and finance institutions, including serving as chairman of semiconductor company STMicroelectronics.
-
B.
Grégory Garestier
Grégory Garestier is a French local politician who serves as the mayor of the commune of Maurepas in the Yvelines department.
-
C.
Laurent Barès
Laurent Barès is a French cinematographer known for his work on genre films, particularly in horror and action.
-
D.
Laurent Vastel
Laurent Vastel is a French local politician who serves as the mayor of the Paris suburb Fontenay-aux-Roses.
-
E.
Laurent Jouvenet
Laurent Jouvenet was a French painter of the 17th century, known as the father of the more famous Baroque artist Jean Jouvenet.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Nicolas Bérauld Triple: [Étienne Dolet, studentOf, Nicolas Bérauld]
Generated description
Nicolas Bérauld was a French Renaissance humanist scholar and teacher known for mentoring figures such as the printer and humanist Étienne Dolet.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nicolas Bérauld Target entity description: Nicolas Bérauld was a French Renaissance humanist scholar and teacher known for mentoring figures such as the printer and humanist Étienne Dolet.
-
A.
Nicolas Dufourcq
Nicolas Dufourcq is a French business executive known for leading major technology and finance institutions, including serving as chairman of semiconductor company STMicroelectronics.
-
B.
Grégory Garestier
Grégory Garestier is a French local politician who serves as the mayor of the commune of Maurepas in the Yvelines department.
-
C.
Laurent Barès
Laurent Barès is a French cinematographer known for his work on genre films, particularly in horror and action.
-
D.
Laurent Vastel
Laurent Vastel is a French local politician who serves as the mayor of the Paris suburb Fontenay-aux-Roses.
-
E.
Laurent Jouvenet
Laurent Jouvenet was a French painter of the 17th century, known as the father of the more famous Baroque artist Jean Jouvenet.
- F. None of above. chosen
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_69c6995f9c60819092e386192bd63c6f |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c7035df9348190ad3f3d845207bf4d |
completed | March 27, 2026, 10:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c998ad1ee08190bbde7900f1bb34bf |
completed | March 29, 2026, 9:25 p.m. |
| NEDg | Description generation | batch_69c99a35420481909fe126b951709941 |
completed | March 29, 2026, 9:31 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c99a8c26b08190bfcc594ff61edfff |
completed | March 29, 2026, 9:33 p.m. |
Created at: March 27, 2026, 4:07 p.m.