Triple
T7279528
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tiger Lake |
E163110
|
entity |
| Predicate | supports |
P516
|
FINISHED |
| Object | OpenCL |
E163108
|
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: OpenCL | Statement: [Tiger Lake, supports, OpenCL]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: OpenCL Context triple: [Tiger Lake, supports, OpenCL]
-
A.
OpenCL
chosen
OpenCL is an open, cross-platform framework for writing programs that execute across heterogeneous systems including CPUs, GPUs, and other processors.
-
B.
SYCL
SYCL is a C++-based, cross-platform abstraction layer for heterogeneous parallel programming, designed to enable single-source development for CPUs, GPUs, and other accelerators.
-
C.
NVIDIA CUDA
NVIDIA CUDA is a parallel computing platform and programming model that enables developers to use NVIDIA GPUs for general-purpose high-performance computing.
-
D.
OpenACC
OpenACC is a directive-based parallel programming standard designed to simplify the development of portable, high-performance code on heterogeneous systems such as GPUs and multicore CPUs.
-
E.
NVIDIA OptiX
NVIDIA OptiX is a GPU-accelerated, programmable ray tracing engine and API from NVIDIA used to build high-performance, photorealistic rendering and simulation applications.
- 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_69c6885c5964819085b209701769877f |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6eb339b1081909f648864e210f98e |
completed | March 27, 2026, 8:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7eedbbc3c81909a02c4fb63e428c0 |
completed | March 28, 2026, 3:08 p.m. |
Created at: March 27, 2026, 2:59 p.m.