Triple
T4326082
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TPUs (via XLA integrations) |
E96636
|
entity |
| Predicate | targetHardware |
P5090
|
FINISHED |
| Object | Google TPU |
E356779
|
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: Google TPU | Statement: [TPUs (via XLA integrations), targetHardware, Google TPU]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Google TPU Context triple: [TPUs (via XLA integrations), targetHardware, Google TPU]
-
A.
Google Tensor
Google Tensor is Google's custom-designed system-on-a-chip (SoC) platform created to power Pixel devices with advanced AI and machine learning capabilities.
-
B.
Graphcore
Graphcore is a British semiconductor company that develops specialized intelligence processing units (IPUs) and systems designed to accelerate artificial intelligence and machine learning workloads.
-
C.
Google Brain
Google Brain is a deep learning research team at Google that pioneered many advances in neural networks and artificial intelligence.
-
D.
Tensor Processing Unit
chosen
A Tensor Processing Unit (TPU) is a specialized AI accelerator chip designed by Google to efficiently perform large-scale machine learning computations, particularly for neural networks.
-
E.
NVIDIA DGX
NVIDIA DGX is a line of high-performance, AI-optimized computing systems designed for training and deploying large-scale machine learning and deep learning models.
- 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_69b34542fd908190b11b08faad8decfd |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3513020f481909ff2fec3934f3002 |
completed | March 12, 2026, 11:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5d09861a4819086a88bb42a8ea2e4 |
completed | March 14, 2026, 9:18 p.m. |
Created at: March 12, 2026, 11:13 p.m.