Triple
T4277371
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TPU |
E97074
|
entity |
| Predicate | hasGeneration |
P455
|
FINISHED |
| Object | TPU v2 |
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: TPU v2 | Statement: [TPU, hasGeneration, TPU v2]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TPU v2 Context triple: [TPU, hasGeneration, TPU v2]
-
A.
TPU
A TPU (Tensor Processing Unit) is a specialized hardware accelerator designed by Google to efficiently perform large-scale machine learning and deep learning computations.
-
B.
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.
-
C.
GPT-2
GPT-2 is a large transformer-based language model known for generating coherent, human-like text and sparking widespread discussion about the implications of advanced AI text generation.
-
D.
Pegasos II
Pegasos II is a PowerPC-based computer mainboard developed by Genesi that became popular as a hardware platform for alternative operating systems such as AmigaOS and MorphOS.
-
E.
Calliope mini
Calliope mini is a small educational microcontroller board designed to teach children and beginners programming and electronics through interactive projects.
- 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_69b34544be3c819084d1ab82d29f90c5 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3501ef1388190b0c968b069014a59 |
completed | March 12, 2026, 11:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5b7b3b52c8190ae7c05448faf5558 |
completed | March 14, 2026, 7:32 p.m. |
Created at: March 12, 2026, 11:07 p.m.