Triple
T109273
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wizards District Gaming |
E2207
|
entity |
| Predicate | hasEsport |
P5865
|
FINISHED |
| Object | basketball simulation |
—
|
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: basketball simulation | Statement: [Wizards District Gaming, hasEsport, basketball simulation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEsport Context triple: [Wizards District Gaming, hasEsport, basketball simulation]
-
A.
sponsorSport
Indicates that one entity financially or materially supports a sport or sporting activity, typically in exchange for promotion or association.
-
B.
hasAthletics
Indicates that an entity participates in, is associated with, or offers athletics-related activities or programs.
-
C.
sportCategory
Indicates that one entity is classified as a type or category of sport to which the other entity (typically a specific sport or sporting event) belongs.
-
D.
primarySport
Indicates the main sport with which an entity (such as a person, team, or organization) is most closely associated or primarily involved.
-
E.
sportOwned
Indicates that one entity possesses ownership or control over a particular sport.
- 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_69a24fcdaeb48190a2d796677e4b3281 |
completed | Feb. 28, 2026, 2:15 a.m. |
| NER | Named-entity recognition | batch_69a25711f6788190a22252ea3a3af394 |
completed | Feb. 28, 2026, 2:46 a.m. |
| PD | Predicate disambiguation | batch_69a2563fd2fc819090265edbfe3092d6 |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a2570f45bc81909ebba7ee5f602976 |
completed | Feb. 28, 2026, 2:46 a.m. |
Created at: Feb. 28, 2026, 2:20 a.m.