Triple
T7874749
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Adam: A Method for Stochastic Optimization |
E182822
|
entity |
| Predicate | author |
P4
|
FINISHED |
| Object | Diederik P. Kingma |
E182823
|
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: Diederik P. Kingma | Statement: [Adam: A Method for Stochastic Optimization, author, Diederik P. Kingma]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Diederik P. Kingma Context triple: [Adam: A Method for Stochastic Optimization, author, Diederik P. Kingma]
-
A.
Diederik P. Kingma
chosen
Diederik P. Kingma is a machine learning researcher best known for co-developing the Adam optimization algorithm and the variational autoencoder (VAE) framework.
-
B.
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."
-
C.
Ilya Sutskever
Ilya Sutskever is a leading artificial intelligence researcher and co-founder of OpenAI, known for his pioneering work in deep learning and neural networks.
-
D.
Nicolas Heess
Nicolas Heess is a machine learning researcher known for his work in deep reinforcement learning, including contributions to algorithms such as Deep Deterministic Policy Gradient (DDPG).
-
E.
Jakob Uszkoreit
Jakob Uszkoreit is a computer scientist and AI researcher best known as one of the co-authors of the seminal "Attention Is All You Need" paper that introduced the Transformer 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_69ca828a17248190b46defe758bc5ad3 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb39a961188190b2f12f8fe5d66641 |
completed | March 31, 2026, 3:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cbdf9535c48190a73653a773553d01 |
completed | March 31, 2026, 2:52 p.m. |
Created at: March 30, 2026, 4:56 p.m.