Triple
T11957857
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mesa 3D |
E284597
|
entity |
| Predicate | supportsVendor |
P79287
|
FINISHED |
| Object | Intel GPUs |
E29764
|
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: Intel GPUs | Statement: [Mesa 3D, supportsVendor, Intel GPUs]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Intel GPUs Context triple: [Mesa 3D, supportsVendor, Intel GPUs]
-
A.
Intel Arc
chosen
Intel Arc is a line of discrete graphics processing units (GPUs) developed by Intel for gaming, content creation, and high-performance graphics workloads.
-
B.
GPUS
GPUS is a progressive U.S. political party focused on environmentalism, social justice, grassroots democracy, and nonviolence.
-
C.
GPU
The GPU (State Political Directorate) was the Soviet Union’s early secret police and intelligence agency that operated in the 1920s, overseeing political repression and internal security before later reorganizations.
-
D.
GPU
GPU is the vehicle registration code used on license plates for cars registered in Poland’s Pomeranian Voivodeship.
-
E.
GPU
A GPU (Graphics Processing Unit) is a highly parallel processor originally designed for rendering graphics that is now widely used to accelerate compute-intensive tasks such as machine learning, scientific simulations, and video processing.
- 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_69d6ab2db38c8190b1f0ed6663ef8ada |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903681a00819098c2b5260e2ef834 |
completed | April 10, 2026, 2:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f459210d1c8190953cd01da3d2ad04 |
completed | May 1, 2026, 7:41 a.m. |
Created at: April 8, 2026, 9:45 p.m.