Triple
T1122746
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jerry Reinsdorf |
E24647
|
entity |
| Predicate | typeOfBusinessActivity |
P1099
|
FINISHED |
| Object | team ownership and management |
—
|
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: team ownership and management | Statement: [Jerry Reinsdorf, typeOfBusinessActivity, team ownership and management]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfBusinessActivity Context triple: [Jerry Reinsdorf, typeOfBusinessActivity, team ownership and management]
-
A.
economicClassification
Indicates how an entity is categorized based on its economic characteristics, status, or role within an economic system.
-
B.
businessFunction
Indicates the specific role, activity, or operational function that an entity performs within a business context.
-
C.
hasEconomicActivity
chosen
Indicates that an entity engages in, supports, or is associated with a specific type of economic activity or business operation.
-
D.
hasTypeOfOrganization
Indicates that an entity is classified as belonging to a particular type or category of organization.
-
E.
employerType
Indicates the classification or category of an employer in relation to the entity (e.g., public, private, nonprofit, self-employed).
- 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_69a4940712c88190aa244f3fc6070a65 |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bc4bc21881909dcfe628f59f3e8c |
completed | March 1, 2026, 10:23 p.m. |
| PD | Predicate disambiguation | batch_69a4bb4749ac8190b0fbddac2e9b2586 |
completed | March 1, 2026, 10:18 p.m. |
Created at: March 1, 2026, 7:44 p.m.