Triple
T16895859
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yannick Jauzion |
E424297
|
entity |
| Predicate | hasNotableAchievements |
P124908
|
FINISHED |
| Object | multiple titles with Stade Toulousain |
—
|
LITERAL 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: multiple titles with Stade Toulousain | Statement: [Yannick Jauzion, hasNotableAchievements, multiple titles with Stade Toulousain]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableAchievements Context triple: [Yannick Jauzion, hasNotableAchievements, multiple titles with Stade Toulousain]
-
A.
hasReferentNotableAchievement
Indicates that an entity’s referent is associated with a specific notable achievement or accomplishment.
-
B.
hasNotableYear
Indicates that an entity is associated with a specific year that is particularly significant or noteworthy for it.
-
C.
hasNotablePerformance
Indicates that an entity has delivered a performance that is distinguished, remarkable, or otherwise noteworthy in a particular context.
-
D.
hasNotableCredit
Indicates that an entity is recognized for having a significant or noteworthy contribution, role, or acknowledgment associated with it.
-
E.
hasNotableWorkSection
Indicates that a notable work is associated with a specific section or part of a larger work or document.
- F. None of above. chosen
Provenance (4 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_69d889da3e8c8190a2b118f383f0beac |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e3c8d7aec88190888f13601acbcd77 |
completed | April 18, 2026, 6:09 p.m. |
| PD | Predicate disambiguation | batch_69e32b90ec3c819099c51bb7baf2984c |
completed | April 18, 2026, 6:58 a.m. |
| PDg | Predicate description generation | batch_69e32e2c07b081908c8fee9f5507bb9e |
completed | April 18, 2026, 7:09 a.m. |
Created at: April 10, 2026, 5:29 a.m.