Triple
T12323423
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amazon Neptune |
E293773
|
entity |
| Predicate | integratesWith |
P1075
|
FINISHED |
| Object | Amazon SageMaker |
E293756
|
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: Amazon SageMaker | Statement: [Amazon Neptune, integratesWith, Amazon SageMaker]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Amazon SageMaker Context triple: [Amazon Neptune, integratesWith, Amazon SageMaker]
-
A.
Amazon SageMaker
chosen
Amazon SageMaker is a fully managed cloud service that enables developers and data scientists to build, train, and deploy machine learning models at scale.
-
B.
SageMaker Studio
SageMaker Studio is Amazon SageMaker’s web-based integrated development environment (IDE) for building, training, and deploying machine learning models at scale.
-
C.
SageMaker Real-time Inference
SageMaker Real-time Inference is a managed Amazon SageMaker capability that lets you deploy machine learning models as always-on, low-latency APIs for real-time prediction workloads.
-
D.
SageMaker Profiler
SageMaker Profiler is a performance profiling tool in Amazon SageMaker that helps analyze and optimize the resource usage and efficiency of machine learning training jobs.
-
E.
Landing AI
Landing AI is a technology company focused on making artificial intelligence accessible to traditional industries by helping them build and deploy practical AI solutions, particularly in manufacturing and computer vision.
- 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_69d6ab6ae0dc8190b1522a9c1c55c114 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f4d7dac81909ff10e64e229ef33 |
completed | April 10, 2026, 6:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6346a3f34819091882004ab558347 |
completed | May 2, 2026, 5:29 p.m. |
Created at: April 8, 2026, 9:53 p.m.