Triple
T11003418
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Łukasz Kaiser |
E260054
|
entity |
| Predicate | developed |
P73
|
FINISHED |
| Object | Tensor2Tensor |
E899031
|
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: Tensor2Tensor | Statement: [Łukasz Kaiser, developed, Tensor2Tensor]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tensor2Tensor Context triple: [Łukasz Kaiser, developed, Tensor2Tensor]
-
A.
Tensor2Tensor library
chosen
Tensor2Tensor library is an open-source deep learning toolkit from Google designed to simplify training and sharing state-of-the-art neural network models, particularly for sequence-to-sequence tasks like machine translation.
-
B.
Tensor2Tensor for Neural Machine Translation
"Tensor2Tensor for Neural Machine Translation" is a research work introducing a modular, scalable library and methodology for training state-of-the-art neural machine translation models.
-
C.
TensorFlow Serving
TensorFlow Serving is a flexible, high-performance system for deploying and serving machine learning models in production, particularly those built with TensorFlow.
-
D.
TensorFlow Estimators
TensorFlow Estimators are a high-level TensorFlow API that simplifies building, training, and deploying machine learning models with standardized workflows and production-ready features.
-
E.
TensorFlow Extended
TensorFlow Extended (TFX) is an end-to-end platform for deploying, managing, and scaling production machine learning pipelines built on TensorFlow.
- 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.