Triple
T12455383
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Olivier Giroud |
E297641
|
entity |
| Predicate | shirtNumberForFrance |
P2651
|
FINISHED |
| Object | 9 |
—
|
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: 9 | Statement: [Olivier Giroud, shirtNumberForFrance, 9]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: shirtNumberForFrance Context triple: [Olivier Giroud, shirtNumberForFrance, 9]
-
A.
shirtNumberType
Indicates the type or category of a shirt number assigned to an entity (for example, a player’s jersey number type).
-
B.
jerseyNumber
chosen
Indicates the specific uniform number assigned to and worn by an individual, typically in a sports context.
-
C.
shirtNumberTradition
Indicates a conventional or historically established assignment or significance of a particular shirt number within a team or sport.
-
D.
jerseyNumberStyle
Indicates the visual design or formatting style used for displaying a player’s jersey number.
-
E.
pointsClassificationJerseyColor
Indicates the color of the jersey awarded to the leader of the points classification in a race or competition.
- F. None of above.
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_69d6ada166c48190b902972cd2408fa3 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d95151e7348190a1d4953a8b416a13 |
completed | April 10, 2026, 7:36 p.m. |
| PD | Predicate disambiguation | batch_69d94d3c27a08190a0237200203e476d |
completed | April 10, 2026, 7:19 p.m. |
Created at: April 8, 2026, 9:56 p.m.