Triple
T37462289
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Awaken the Makers |
E930946
|
entity |
| Predicate | rewardEffect |
P113458
|
FINISHED |
| Object | Adds Amara, Warden of Hope to your hand upon completion |
—
|
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: Adds Amara, Warden of Hope to your hand upon completion | Statement: [Awaken the Makers, rewardEffect, Adds Amara, Warden of Hope to your hand upon completion]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rewardEffect Context triple: [Awaken the Makers, rewardEffect, Adds Amara, Warden of Hope to your hand upon completion]
-
A.
awardEffect
chosen
Indicates that one entity confers or grants a benefit, recognition, or reward that has a particular impact or consequence on another entity.
-
B.
rewardUse
Indicates that one entity grants or provides a reward in response to the use or utilization of another entity.
-
C.
rewardPotential
Indicates the degree to which an action, option, or outcome is expected to yield positive benefits or rewards.
-
D.
rewardBrand
Indicates that one entity grants or associates a reward with a particular brand.
-
E.
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.
- 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_69f76ec1a1148190b0a961f188d621b0 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fbbc49da8c8190902bbb05d2477cab |
completed | May 6, 2026, 10:10 p.m. |
| PD | Predicate disambiguation | batch_69fbb13f34b08190bbbb220ac1e6e666 |
completed | May 6, 2026, 9:23 p.m. |
Created at: May 3, 2026, 4:17 p.m.