Triple
T24599488
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tampa Bay Sports and Entertainment |
E608780
|
entity |
| Predicate | sportOfPrimaryAsset |
P1080
|
FINISHED |
| Object | ice hockey |
—
|
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: ice hockey | Statement: [Tampa Bay Sports and Entertainment, sportOfPrimaryAsset, ice hockey]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sportOfPrimaryAsset Context triple: [Tampa Bay Sports and Entertainment, sportOfPrimaryAsset, ice hockey]
-
A.
primarySportsAsset
Indicates that one entity serves as the main or most important sports-related asset associated with another entity.
-
B.
primarySport
chosen
Indicates the main sport with which an entity (such as a person, team, or organization) is most closely associated or primarily involved.
-
C.
primarySports
Indicates that a particular sport is the main or most important sport associated with an entity (such as a person, team, or organization).
-
D.
sportsName
Indicates the specific sport associated with or played in a given context or event.
-
E.
originalSport
Indicates that one sport is the initial or primary sport associated with an entity, often before any change, adaptation, or transition to another sport.
- 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_69e2c4cf54248190af7b0c2d9ade9830 |
completed | April 17, 2026, 11:39 p.m. |
| NER | Named-entity recognition | batch_69f2be044d4c819094e14eda28d371a7 |
completed | April 30, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69f2a6ca751c8190a040c10d701ecf3a |
completed | April 30, 2026, 12:48 a.m. |
Created at: April 18, 2026, 2:30 a.m.