Triple
T21380269
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Donald Tokowitz |
E527331
|
entity |
| Predicate | legalSanction |
P59651
|
FINISHED |
| Object | lifetime ban from the NBA |
—
|
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: lifetime ban from the NBA | Statement: [Donald Tokowitz, legalSanction, lifetime ban from the NBA]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: legalSanction Context triple: [Donald Tokowitz, legalSanction, lifetime ban from the NBA]
-
A.
employerSanctionsDescription
Indicates a description of penalties or disciplinary actions imposed by an employer in response to certain behaviors, violations, or conditions.
-
B.
isSanctionedBy
chosen
Indicates that an entity is subject to official penalties, restrictions, or punitive measures imposed by another authority or organization.
-
C.
typeOfSanction
Indicates the specific category or kind of sanction that is applied in a given situation.
-
D.
sanction
Indicates the imposition of an official penalty or restrictive measure by an authority in response to certain actions or behaviors.
-
E.
canBeSanctionedFor
Indicates that an entity is subject to penalties or disciplinary measures as a consequence of a specified action, behavior, or condition.
- 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_69e0b51f363c8190944000ab5523b02b |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e8b0cdab8c8190a7eebe6e5961ee75 |
completed | April 22, 2026, 11:28 a.m. |
| PD | Predicate disambiguation | batch_69e6162bbfc88190a3e75859941b2638 |
completed | April 20, 2026, 12:03 p.m. |
Created at: April 16, 2026, 5:11 p.m.