Triple
T14276494
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Matrix (Doctor Who) |
E353928
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | Amplified Panatropic Computation Network |
E353930
|
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: Amplified Panatropic Computation Network | Statement: [The Matrix (Doctor Who), alsoKnownAs, Amplified Panatropic Computation Network]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Amplified Panatropic Computation Network Context triple: [The Matrix (Doctor Who), alsoKnownAs, Amplified Panatropic Computation Network]
-
A.
the Amplified Panatropic Computation Network
chosen
The Amplified Panatropic Computation Network is a vast, hyper-advanced Gallifreyan data and information processing system used by the Time Lords in the Doctor Who universe.
-
B.
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.
-
C.
SyNAPSE neuromorphic computing program
The SyNAPSE neuromorphic computing program is a DARPA initiative to develop brain-inspired electronic systems that emulate neural architectures for highly efficient, scalable cognitive computing.
-
D.
AmoebaNet
AmoebaNet is a convolutional neural network architecture discovered through evolutionary neural architecture search, known for achieving state-of-the-art image classification performance.
-
E.
Intriguing properties of neural networks
"Intriguing properties of neural networks" is a highly influential research paper that revealed surprising vulnerabilities and behaviors of deep neural networks, particularly their susceptibility to adversarial examples.
- 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_69d8278d25148190abf1a8c8f5f533ad |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de6583f0ec81909ebfc7a2c6351ff8 |
completed | April 14, 2026, 4:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd326f62b4819084b1e984678991ae |
completed | May 8, 2026, 12:46 a.m. |
Created at: April 10, 2026, 1:10 a.m.