Triple
T4443370
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Random |
E96222
|
entity |
| Predicate | definesType |
P56536
|
FINISHED |
| Object | TaskLocalRNG |
E96222
|
NE 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: TaskLocalRNG | Statement: [Random, definesType, TaskLocalRNG]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TaskLocalRNG Context triple: [Random, definesType, TaskLocalRNG]
-
A.
Random Dent
Random Dent is a character in Douglas Adams' "The Hitchhiker's Guide to the Galaxy" series, known as the daughter of Arthur Dent and Trillian.
-
B.
Random
Random is a fictional character who serves as the main protagonist in the story "Out of the Blue."
-
C.
Random
chosen
Random is a Julia standard library module that provides functionality for generating and manipulating random numbers and random processes.
-
D.
cuRAND
cuRAND is NVIDIA's GPU-accelerated random number generation library designed to efficiently produce high-quality random numbers for parallel applications using CUDA.
-
E.
jax.random
jax.random is JAX’s module for generating and manipulating pseudo-random numbers in a functional, reproducible way using PRNG keys.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69b345415ba481908df738e7174448ba |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3564216b081908c41109100b36862 |
completed | March 13, 2026, 12:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b61382d00481908b7c84f337b5cad7 |
completed | March 15, 2026, 2:03 a.m. |
Created at: March 12, 2026, 11:32 p.m.