Triple
T646379
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Mara |
E11249
|
entity |
| Predicate | genreOfBusiness |
P71
|
FINISHED |
| Object | professional sports 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: professional sports management | Statement: [John Mara, genreOfBusiness, professional sports management]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genreOfBusiness Context triple: [John Mara, genreOfBusiness, professional sports management]
-
A.
businessBase
Indicates that one entity serves as the primary business foundation, core location, or main operational base for another entity.
-
B.
economicClassification
Indicates how an entity is categorized based on its economic characteristics, status, or role within an economic system.
-
C.
businessFunction
Indicates the specific role, activity, or operational function that an entity performs within a business context.
-
D.
category
Indicates that one entity is classified as a member or type within the grouping or class defined by another entity.
-
E.
sector
chosen
Indicates that an entity operates in, belongs to, or is associated with a particular economic or industrial sector.
- 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_69a493266a2881909daf4c40f719dee8 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49f1b24b08190897d8aedb877bd83 |
completed | March 1, 2026, 8:18 p.m. |
| PD | Predicate disambiguation | batch_69a49d0c0dcc8190849211d45489a5a7 |
completed | March 1, 2026, 8:09 p.m. |
Created at: March 1, 2026, 7:36 p.m.