Triple
T4586042
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Double DQN |
E101969
|
entity |
| Predicate | commonlyUses |
P11801
|
FINISHED |
| Object | epsilon-greedy exploration |
—
|
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: epsilon-greedy exploration | Statement: [Double DQN, commonlyUses, epsilon-greedy exploration]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: commonlyUses Context triple: [Double DQN, commonlyUses, epsilon-greedy exploration]
-
A.
widelyUsedIn
chosen
Indicates that something is commonly or extensively utilized within a particular context, domain, or group.
-
B.
mainlyUses
Indicates that one entity primarily relies on, employs, or utilizes another entity as its main tool, method, resource, or medium.
-
C.
usedWith
Indicates that one entity is typically or appropriately employed together with another entity in a combined or complementary use.
-
D.
moreCommonIn
Indicates that something occurs with greater frequency or prevalence in one group, context, or location than in another.
-
E.
commonIn
Indicates that something frequently occurs, appears, or is found within a specified context, group, or environment.
- 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_69bd43d4ce208190b53158c882b222e3 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd5906a43c81908fb11bf8f94be122 |
completed | March 20, 2026, 2:26 p.m. |
| PD | Predicate disambiguation | batch_69bd522acbcc8190bf24d9517793a2c1 |
completed | March 20, 2026, 1:56 p.m. |
Created at: March 20, 2026, 1:10 p.m.