Triple
T215013
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ovi |
E4799
|
entity |
| Predicate | associatedFranchise |
P9673
|
FINISHED |
| Object | Washington Capitals franchise icon |
—
|
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: Washington Capitals franchise icon | Statement: [Ovi, associatedFranchise, Washington Capitals franchise icon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedFranchise Context triple: [Ovi, associatedFranchise, Washington Capitals franchise icon]
-
A.
franchiseOf
Indicates that one entity operates as a franchise belonging to or licensed by another entity.
-
B.
affectedFranchise
Indicates that one entity has an impact on, or brings about a change in the status or condition of, a franchise.
-
C.
ownsMajorFranchiseIn
Indicates that an entity has controlling or primary ownership of a major franchise operating within a specified location or jurisdiction.
-
D.
affiliateLeague
Indicates that one sports organization or team is formally associated with and operates under the umbrella or partnership of a particular league.
-
E.
playsForFranchise
Indicates that one entity is an athlete or performer who is a member of, or competes on behalf of, a particular sports franchise or team.
- 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_69a2575cb1dc8190a01ad332426dc339 |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a25dcd2b208190855d5d8d70a3acfc |
completed | Feb. 28, 2026, 3:15 a.m. |
| PD | Predicate disambiguation | batch_69a25b52190481908f299d26122bafd2 |
completed | Feb. 28, 2026, 3:04 a.m. |
| PDg | Predicate description generation | batch_69a25dcba5148190ab80fd14c7cf4bb4 |
completed | Feb. 28, 2026, 3:15 a.m. |
Created at: Feb. 28, 2026, 2:52 a.m.