Triple
T5927630
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rupesh Kumar Srivastava |
E131852
|
entity |
| Predicate | collaboratedWith |
P435
|
FINISHED |
| Object | Christian Szegedy |
E19896
|
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: Christian Szegedy | Statement: [Rupesh Kumar Srivastava, collaboratedWith, Christian Szegedy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Christian Szegedy Context triple: [Rupesh Kumar Srivastava, collaboratedWith, Christian Szegedy]
-
A.
Christian Szegedy
chosen
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.
-
B.
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.
-
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.
Karen Simonyan
Karen Simonyan is a computer scientist and deep learning researcher known for influential work in neural network architectures and generative models, including contributions to systems like WaveNet.
-
E.
Jonathon Shlens
Jonathon Shlens is a computer scientist and researcher known for his contributions to deep learning and computer vision, including influential work at Google.
- 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_69c0085b75e88190a632f9691f9da48b |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0385592b48190a885efb9549d88c7 |
completed | March 22, 2026, 6:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0c05460c481908f3efde19e3ffa2a |
completed | March 23, 2026, 4:23 a.m. |
Created at: March 22, 2026, 4 p.m.