Triple
T3803466
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Julien BriseBois |
E91745
|
entity |
| Predicate | typeOfOrganizationManaged |
P36102
|
FINISHED |
| Object | professional ice hockey team |
—
|
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: professional ice hockey team | Statement: [Julien BriseBois, typeOfOrganizationManaged, professional ice hockey team]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfOrganizationManaged Context triple: [Julien BriseBois, typeOfOrganizationManaged, professional ice hockey team]
-
A.
hasTypeOfOrganization
Indicates that an entity is classified as belonging to a particular type or category of organization.
-
B.
organizationTypeGoverned
Indicates that one entity governs or has authoritative control over a specific type or category of organization.
-
C.
typeOfSportOrganizationManaged
chosen
Indicates the specific kind of sports organization that an entity is responsible for managing.
-
D.
organizationType
Indicates the specific category or classification of an organization in terms of its nature, structure, or primary function.
-
E.
containsOrganizationType
Indicates that an entity includes or is associated with an organization of a specified organizational type (e.g., company, nonprofit, government agency).
- 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_69aed96354f48190a768966d6bd19b04 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aee8db8a288190afd1e3b9dcf02e97 |
completed | March 9, 2026, 3:35 p.m. |
| PD | Predicate disambiguation | batch_69aee7461abc8190945716f4b93e1a18 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:15 p.m.