Triple
T15542921
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joubert |
E370525
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Laurent Joubert
Laurent Joubert was a 16th-century French physician and writer known for his influential medical texts and his role as personal doctor to King Charles IX.
|
E1163342
|
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: Laurent Joubert | Statement: [Joubert, hasNotableBearer, Laurent Joubert]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Laurent Joubert Context triple: [Joubert, hasNotableBearer, Laurent Joubert]
-
A.
Fabien Galthié
Fabien Galthié is a former French international scrum-half and prominent rugby union coach, best known for leading the France national team in the modern era.
-
B.
Laurent Grangeon
Laurent Grangeon is a musician best known as a member of the rock band Wakrat.
-
C.
Guy Novès
Guy Novès is a highly successful French rugby union coach and former player, best known for leading Stade Toulousain to numerous domestic and European titles.
-
D.
Christophe Julien
Christophe Julien is a French film composer known for creating original scores for movies such as "Two Lovers."
-
E.
Stéphane Fontaine
Stéphane Fontaine is a French cinematographer known for his acclaimed work on contemporary European cinema, including collaborations with prominent auteurs.
- 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: Laurent Joubert Triple: [Joubert, hasNotableBearer, Laurent Joubert]
Generated description
Laurent Joubert was a 16th-century French physician and writer known for his influential medical texts and his role as personal doctor to King Charles IX.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Laurent Joubert Target entity description: Laurent Joubert was a 16th-century French physician and writer known for his influential medical texts and his role as personal doctor to King Charles IX.
-
A.
Fabien Galthié
Fabien Galthié is a former French international scrum-half and prominent rugby union coach, best known for leading the France national team in the modern era.
-
B.
Laurent Grangeon
Laurent Grangeon is a musician best known as a member of the rock band Wakrat.
-
C.
Guy Novès
Guy Novès is a highly successful French rugby union coach and former player, best known for leading Stade Toulousain to numerous domestic and European titles.
-
D.
Christophe Julien
Christophe Julien is a French film composer known for creating original scores for movies such as "Two Lovers."
-
E.
Stéphane Fontaine
Stéphane Fontaine is a French cinematographer known for his acclaimed work on contemporary European cinema, including collaborations with prominent auteurs.
- 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_69d85cc521a08190921fb50319dddc34 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04432c3808190bb5b653bf8de30c6 |
completed | April 16, 2026, 2:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff4558677881908704ac86c12e1fc4 |
completed | May 9, 2026, 2:31 p.m. |
| NEDg | Description generation | batch_69ff468d1db88190ad71bc6780df5439 |
completed | May 9, 2026, 2:37 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff472fb24c8190912755bd95ef50c9 |
completed | May 9, 2026, 2:39 p.m. |
Created at: April 10, 2026, 4:07 a.m.