Triple
T34008895
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gambler’s Roll |
E872046
|
entity |
| Predicate | hasOptimalTotal |
P7664
|
FINISHED |
| Object | lucky number |
—
|
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: lucky number | Statement: [Gambler’s Roll, hasOptimalTotal, lucky number]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOptimalTotal Context triple: [Gambler’s Roll, hasOptimalTotal, lucky number]
-
A.
hasOptimalPlayProperty
Indicates that the subject possesses a characteristic or condition under which its behavior, strategy, or outcome is considered optimally effective according to defined criteria.
-
B.
hasTotalNumber
chosen
Indicates that an entity is associated with a specific overall count or sum of items, elements, or units.
-
C.
typeOfOptimality
Indicates that one entity specifies the particular notion or criterion of optimality that characterizes another entity’s optimal status or solution.
-
D.
hasTotalSize
Indicates that an entity possesses or is associated with a specific overall size or aggregate measurement.
-
E.
canBeOptimizedFor
Indicates that one entity is capable of being improved or adjusted to perform better with respect to another specified criterion, context, or target.
- 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_69f349a08848819084b348d64c1879c3 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fbad1e94988190b86d447a68e65067 |
completed | May 6, 2026, 9:05 p.m. |
| PD | Predicate disambiguation | batch_69fba881b8e0819094790935152b99a1 |
completed | May 6, 2026, 8:45 p.m. |
Created at: May 1, 2026, 1:51 a.m.