Triple
T19159934
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mark Noble |
E469024
|
entity |
| Predicate | shirtNumberAtIpswichTown |
P2651
|
FINISHED |
| Object | 16 |
—
|
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: 16 | Statement: [Mark Noble, shirtNumberAtIpswichTown, 16]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: shirtNumberAtIpswichTown Context triple: [Mark Noble, shirtNumberAtIpswichTown, 16]
-
A.
shirtNumberTradition
Indicates a conventional or historically established assignment or significance of a particular shirt number within a team or sport.
-
B.
shirtNumberODI
Indicates the jersey number a player wears in One Day International (ODI) cricket matches.
-
C.
shirtNumberType
Indicates the type or category of a shirt number assigned to an entity (for example, a player’s jersey number type).
-
D.
jerseyNumber
chosen
Indicates the specific uniform number assigned to and worn by an individual, typically in a sports context.
-
E.
shirtNumberInnovation
Indicates an association where an entity’s shirt number is linked to a novel or unconventional change, method, or feature related to numbering.
- 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_69d8dd084ff48190ac0f8c46ee722629 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5eebc52dc819085666dbbeea365a6 |
completed | April 20, 2026, 9:15 a.m. |
| PD | Predicate disambiguation | batch_69e4b9b83d6881908e6271c620f74100 |
completed | April 19, 2026, 11:17 a.m. |
Created at: April 10, 2026, 12:06 p.m.