Triple
T25307870
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hot Spot |
E634529
|
entity |
| Predicate | randomizationMethod |
P158449
|
FINISHED |
| Object | computerized draw system |
—
|
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: computerized draw system | Statement: [Hot Spot, randomizationMethod, computerized draw system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: randomizationMethod Context triple: [Hot Spot, randomizationMethod, computerized draw system]
-
A.
isRandomized
Indicates that the selection, ordering, or assignment associated with something is determined by a random process rather than a fixed or predetermined rule.
-
B.
introducesRandomnessIn
Indicates that something adds an element of unpredictability or variability into another process, system, or outcome.
-
C.
canBeRandomized
Indicates that the entity is capable of having its state, order, or selection determined by a random process.
-
D.
simulationMethod
Indicates the technique or approach used to perform or implement a simulation.
-
E.
defaultRNGType
Indicates the standard or primary random number generator type that should be used when no specific RNG type is explicitly chosen.
- 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_69e75a972c6481909bc11710e8d30a6c |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f4939c49a48190b9fdc2555273915e |
completed | May 1, 2026, 11:50 a.m. |
| PD | Predicate disambiguation | batch_69f4683472ec8190a483b3b8afe71720 |
completed | May 1, 2026, 8:45 a.m. |
| PDg | Predicate description generation | batch_69f46d361c348190b5fdfd805ecde01b |
completed | May 1, 2026, 9:07 a.m. |
Created at: April 21, 2026, 1:25 p.m.