Triple
T26201083
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wahab Riaz |
E655230
|
entity |
| Predicate | hasMatchTypeSpecialization |
P132627
|
FINISHED |
| Object | limited-overs formats |
—
|
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: limited-overs formats | Statement: [Wahab Riaz, hasMatchTypeSpecialization, limited-overs formats]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMatchTypeSpecialization Context triple: [Wahab Riaz, hasMatchTypeSpecialization, limited-overs formats]
-
A.
isSpecializedFor
Indicates that one entity is specifically adapted, designed, or focused to perform optimally for a particular function, context, or domain associated with another entity.
-
B.
hasTypeOfMatches
chosen
Indicates that one entity has matches that are of a specified type or category in relation to another entity.
-
C.
specializesTo
Indicates that one entity is a more specific or specialized version of another, inheriting its characteristics while adding further constraints or detail.
-
D.
hasSpecializationRequirement
Indicates that an entity requires a specific specialization or field of expertise as a condition for participation, eligibility, or association.
-
E.
hasSpecificity
Indicates that one entity is defined, characterized, or constrained in a more detailed or narrowly focused way relative to another.
- 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_69ee5b48236c81908fe385b6afc4f60b |
completed | April 26, 2026, 6:36 p.m. |
| NER | Named-entity recognition | batch_69fcdf2394748190b35cead3e208447d |
completed | May 7, 2026, 6:51 p.m. |
| PD | Predicate disambiguation | batch_69fcdbe344ec8190a0471911952f4b82 |
completed | May 7, 2026, 6:37 p.m. |
Created at: April 26, 2026, 8:48 p.m.