Triple
T11003424
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Łukasz Kaiser |
E260054
|
entity |
| Predicate | collaboratedWith |
P435
|
FINISHED |
| Object | Jakob Uszkoreit |
E457854
|
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: Jakob Uszkoreit | Statement: [Łukasz Kaiser, collaboratedWith, Jakob Uszkoreit]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jakob Uszkoreit Context triple: [Łukasz Kaiser, collaboratedWith, Jakob Uszkoreit]
-
A.
Jakob Uszkoreit
chosen
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.
-
B.
Dzmitry Bahdanau
Dzmitry Bahdanau is a computer scientist best known for pioneering the neural attention mechanism in sequence-to-sequence models, which transformed neural machine translation and modern 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.
Ilya Goodfellow
Ilya Goodfellow is a machine learning researcher best known for inventing Generative Adversarial Networks (GANs) and contributing to deep learning at organizations like Google and OpenAI.
- 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_69d6aa8a6a548190a750f944ccdc8064 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d797546f448190946ee6442d657dc5 |
completed | April 9, 2026, 12:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e37486b23081909ad282397c50a913 |
completed | April 18, 2026, 12:09 p.m. |
Created at: April 8, 2026, 9:25 p.m.