Triple
T14388387
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tensor SoC family |
E356780
|
entity |
| Predicate | integratesComponent |
P1075
|
FINISHED |
| Object | NPU |
E968294
|
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: NPU | Statement: [Tensor SoC family, integratesComponent, NPU]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: NPU Context triple: [Tensor SoC family, integratesComponent, NPU]
-
A.
NPU
NPU is the commonly used abbreviation for the National Police of Ukraine, the country’s central law enforcement agency responsible for maintaining public order and safety.
-
B.
NPU
NPU is a leading Chinese research university in Xi’an renowned for its strengths in aeronautics, astronautics, and marine engineering.
-
C.
NPU
chosen
An NPU (Neural Processing Unit) is a specialized processor designed to accelerate artificial intelligence and machine learning workloads, particularly neural network computations.
-
D.
DPU
DPU is an Incoterm used in international trade that specifies the seller is responsible for delivering goods unloaded at a named place in the buyer’s country, bearing all risks and costs up to that point.
-
E.
Tensor Processing Unit
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.
- 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_69d827927c988190ad98bb0360981783 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de90283b9c8190b50d30ad58bfe085 |
completed | April 14, 2026, 7:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd551623608190ba1de09b423cc5e1 |
completed | May 8, 2026, 3:14 a.m. |
Created at: April 10, 2026, 1:16 a.m.