Triple
T1171826
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cris Collinsworth |
E24928
|
entity |
| Predicate | businessRole |
P8439
|
FINISHED |
| Object | majority owner of Pro Football Focus |
—
|
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: majority owner of Pro Football Focus | Statement: [Cris Collinsworth, businessRole, majority owner of Pro Football Focus]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: businessRole Context triple: [Cris Collinsworth, businessRole, majority owner of Pro Football Focus]
-
A.
businessFunction
Indicates the specific role, activity, or operational function that an entity performs within a business context.
-
B.
roleInIndustry
chosen
Indicates the specific function, position, or capacity an entity holds within a particular industry or sector.
-
C.
businessBase
Indicates that one entity serves as the primary business foundation, core location, or main operational base for another entity.
-
D.
businessCareer
Indicates a relationship where an entity’s professional life, roles, or progression is specifically within the field of business or commerce.
-
E.
roleInText
Indicates that an entity participates in a text with a specific function or capacity (e.g., author, editor, character).
- 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_69a494082a7c819095004f423f294a64 |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bceb3f188190b8b767380fe5986f |
completed | March 1, 2026, 10:25 p.m. |
| PD | Predicate disambiguation | batch_69a4bb5656948190b0b1d5446ad06005 |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:45 p.m.