Triple
T35664429
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fallout 1st |
E1030524
|
entity |
| Predicate | hasVirtualCurrencyBenefit |
P193682
|
FINISHED |
| Object | Atoms |
—
|
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: Atoms | Statement: [Fallout 1st, hasVirtualCurrencyBenefit, Atoms]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVirtualCurrencyBenefit Context triple: [Fallout 1st, hasVirtualCurrencyBenefit, Atoms]
-
A.
hasBenefit
Indicates that one entity provides an advantage, improvement, or positive outcome to another entity.
-
B.
hasBenefitType
Indicates that an entity is associated with a specific category or type of benefit it provides or receives.
-
C.
canBeRedeemedFor
Indicates that one item, asset, or benefit may be exchanged or converted to obtain another specified item, asset, or benefit.
-
D.
hasBenefitDesign
Indicates that an entity possesses or is associated with a particular benefit-related design or configuration.
-
E.
canBeEarnedBy
Indicates that something (such as a reward, status, or resource) is obtainable through the actions, efforts, or qualifications of a particular 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_69f76e09f87881909c954aaac176c34f |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fd4f39b5008190b83b3227ce22c509 |
completed | May 8, 2026, 2:49 a.m. |
| PD | Predicate disambiguation | batch_69fd4df17c548190a4e2a6fea70f7e10 |
completed | May 8, 2026, 2:44 a.m. |
| PDg | Predicate description generation | batch_69fd4f38728c8190b3271abc80882cfb |
completed | May 8, 2026, 2:49 a.m. |
Created at: May 3, 2026, 4:05 p.m.