Triple
T18705354
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TensorFlow Serving |
E457353
|
entity |
| Predicate | supportsModelFormat |
P8463
|
FINISHED |
| Object | SavedModel |
—
|
NE NERFINISHED |
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: SavedModel | Statement: [TensorFlow Serving, supportsModelFormat, SavedModel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SavedModel Context triple: [TensorFlow Serving, supportsModelFormat, SavedModel]
-
A.
TensorFlow Serving
TensorFlow Serving is a flexible, high-performance system for deploying and serving machine learning models in production, particularly those built with TensorFlow.
-
B.
TensorFlow SavedModel (via conversion)
chosen
TensorFlow SavedModel (via conversion) is a serialized model format from the core TensorFlow ecosystem that can be transformed into a TensorFlow.js-compatible model for deployment in JavaScript environments.
-
C.
TensorFlow Model Garden
TensorFlow Model Garden is a curated collection of state-of-the-art machine learning models, reference implementations, and examples built using TensorFlow to help developers train, evaluate, and deploy advanced AI solutions.
-
D.
NNEF
NNEF (Neural Network Exchange Format) is an open standard from the Khronos Group designed to enable portable, efficient interchange of trained neural network models across different hardware and software platforms.
-
E.
TensorFlow Hub
TensorFlow Hub is a library and online repository of reusable machine learning models and components designed to simplify sharing and deploying pretrained models in TensorFlow applications.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8d392aad081909fe31aa03e6e97d1 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5671665bc8190b9b4a4ce4ec5b2eb |
completed | April 19, 2026, 11:36 p.m. |
Created at: April 10, 2026, 11:49 a.m.