Triple
T4833508
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Intriguing properties of neural networks |
E108000
|
entity |
| Predicate | author |
P4
|
FINISHED |
| Object | Ilya Sutskever |
E11116
|
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: Ilya Sutskever | Statement: [Intriguing properties of neural networks, author, Ilya Sutskever]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ilya Sutskever Context triple: [Intriguing properties of neural networks, author, Ilya Sutskever]
-
A.
Ilya Sutskever
chosen
Ilya Sutskever is a leading artificial intelligence researcher and co-founder of OpenAI, known for his pioneering work in deep learning and neural networks.
-
B.
Volodymyr Mnih
Volodymyr Mnih is a computer scientist and deep learning researcher known for pioneering deep reinforcement learning methods that achieved human-level performance on Atari games.
-
C.
Alex Krizhevsky
Alex Krizhevsky is a computer scientist best known for co-developing the AlexNet convolutional neural network, which revolutionized deep learning in computer vision.
-
D.
Ian Goodfellow
Ian Goodfellow is a machine learning researcher best known for inventing Generative Adversarial Networks (GANs) and co-authoring the influential textbook "Deep Learning."
-
E.
Christian Szegedy
Christian Szegedy is a computer scientist and AI researcher known for his influential work on deep learning and convolutional neural networks, including contributions to the Inception architecture.
- 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_69bd43fbe444819085cb970706ef73f7 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6cca88d88190a8ad6cf7856bdf69 |
completed | March 20, 2026, 3:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be6fa6479c8190b04c2ff50b98ad1d |
completed | March 21, 2026, 10:15 a.m. |
Created at: March 20, 2026, 1:25 p.m.