Triple
T14447899
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Basic Attention Token |
E358253
|
entity |
| Predicate | rewardRecipient |
P114313
|
FINISHED |
| Object | Brave users |
—
|
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: Brave users | Statement: [Basic Attention Token, rewardRecipient, Brave users]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rewardRecipient Context triple: [Basic Attention Token, rewardRecipient, Brave users]
-
A.
rewardFulfilledFor
Indicates that a previously promised or expected reward has been delivered or satisfied for a particular entity.
-
B.
rewardModel
Indicates a relationship where one entity serves as a model or framework for assigning rewards or evaluating outcomes for another entity or process.
-
C.
rewardSignal
Indicates that one entity provides a signal representing feedback or incentive (such as a reward or penalty) to guide another entity’s behavior or learning process.
-
D.
rewardUnit
Indicates that one entity serves as the unit or measure in which a reward is quantified or granted to another entity.
-
E.
rewardMechanism
Indicates a relationship where an entity provides or defines a system of incentives or compensation in response to certain actions, behaviors, or outcomes.
- F. None of above. chosen
Provenance (4 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_69d82794dfa081909b9134ad2e32244b |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de9160126c8190a2862a1a3dde1aff |
completed | April 14, 2026, 7:11 p.m. |
| PD | Predicate disambiguation | batch_69de5c3a02fc819097373f97a260cdeb |
completed | April 14, 2026, 3:24 p.m. |
| PDg | Predicate description generation | batch_69de5fb4de14819092acdecbd201d672 |
completed | April 14, 2026, 3:39 p.m. |
Created at: April 10, 2026, 1:19 a.m.