Triple
T49686
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robert Kraft |
E976
|
entity |
| Predicate | businessSector |
P71
|
FINISHED |
| Object | sports and entertainment |
—
|
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: sports and entertainment | Statement: [Robert Kraft, businessSector, sports and entertainment]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: businessSector Context triple: [Robert Kraft, businessSector, sports and entertainment]
-
A.
sector
chosen
Indicates that an entity operates in, belongs to, or is associated with a particular economic or industrial sector.
-
B.
economicAspect
Indicates that something is related to, characterized by, or has implications for economic factors, conditions, or outcomes.
-
C.
sectorServed
Indicates the industry or economic sector that an entity primarily serves or targets with its activities, products, or services.
-
D.
market
Indicates the act of promoting, advertising, or selling a product, service, or idea to potential buyers or target audiences.
-
E.
businessPartner
Indicates a formal collaborative relationship between two entities that work together in a business context, typically sharing responsibilities, risks, or benefits.
- 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_69a2480baefc81909951b14058479aa2 |
completed | Feb. 28, 2026, 1:42 a.m. |
| NER | Named-entity recognition | batch_69a24b6c9eb88190b2fe85e427f4177a |
completed | Feb. 28, 2026, 1:57 a.m. |
| PD | Predicate disambiguation | batch_69a24ac0fb088190b7a5e87817e8e747 |
completed | Feb. 28, 2026, 1:54 a.m. |
Created at: Feb. 28, 2026, 1:47 a.m.