Triple
T9029662
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | REN |
E216135
|
entity |
| Predicate | utility |
P85768
|
FINISHED |
| Object | pays fees to Darknode operators (directly or indirectly) |
—
|
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: pays fees to Darknode operators (directly or indirectly) | Statement: [REN, utility, pays fees to Darknode operators (directly or indirectly)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: utility Context triple: [REN, utility, pays fees to Darknode operators (directly or indirectly)]
-
A.
uso
Indicates that one entity uses, employs, or makes use of another entity for some purpose or function.
-
B.
usageAmong
Indicates how frequently or in what manner something is used within a particular group, context, or population.
-
C.
purpose
Indicates that one entity exists, is done, or is used in order to achieve, support, or serve the goal, function, or intended outcome of another entity.
-
D.
usageType
Indicates the specific manner, purpose, or context in which something is used or intended to be used.
-
E.
typeOfUtility
Indicates that one entity is a specific kind or category of utility associated with another entity.
- 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_69ca83a5fa88819088144801b4dd7245 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc6a9bcb508190b58751f1772407d4 |
completed | April 1, 2026, 12:45 a.m. |
| PD | Predicate disambiguation | batch_69cc5ee3597c81908919cf866ae95c24 |
completed | March 31, 2026, 11:55 p.m. |
| PDg | Predicate description generation | batch_69cc5f6dec4081909379bd57c02a5710 |
completed | March 31, 2026, 11:57 p.m. |
Created at: March 30, 2026, 7:08 p.m.