Triple
T7110127
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jonny Wilkinson |
E165685
|
entity |
| Predicate | positionSpeciality |
P466
|
FINISHED |
| Object | goal-kicking |
—
|
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: goal-kicking | Statement: [Jonny Wilkinson, positionSpeciality, goal-kicking]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: positionSpeciality Context triple: [Jonny Wilkinson, positionSpeciality, goal-kicking]
-
A.
positionSpecialization
Indicates that one position is a more specialized or focused variant of another, broader position.
-
B.
hasSpecialty
chosen
Indicates that an entity possesses a particular area of expertise, focus, or professional specialization.
-
C.
distanceSpecialism
Indicates a relationship where an entity’s area of specialization is specifically in distance-related aspects (such as distance measurement, analysis, or optimization) within a broader domain.
-
D.
distanceSpecialty
Indicates a relationship where an entity’s specialty or expertise is specifically in the field or domain of distance (e.g., distance learning, distance measurement, or distance-related services).
-
E.
positionSpecific
Indicates that something applies only at, or is defined with respect to, a particular position or location within a larger structure or sequence.
- 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_69c6888120f081908f8f01b201dc4a4c |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e5be09d881909988b5382ffa20ed |
completed | March 27, 2026, 8:17 p.m. |
| PD | Predicate disambiguation | batch_69c6e1c313e481908b61a23fc89f9332 |
completed | March 27, 2026, 8 p.m. |
Created at: March 27, 2026, 2:43 p.m.