Triple
T9674944
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MXNet |
E234123
|
entity |
| Predicate | hasAPI |
P182
|
FINISHED |
| Object | Gluon API |
E814033
|
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: Gluon API | Statement: [MXNet, hasAPI, Gluon API]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gluon API Context triple: [MXNet, hasAPI, Gluon API]
-
A.
Gluon API
chosen
Gluon API is a high-level, imperative deep learning interface designed for building and training neural networks more easily and flexibly on the Apache MXNet framework.
-
B.
Gluon GUI
Gluon GUI is a graphical user interface client for Plastic SCM that provides an easy, visual way to manage version control tasks.
-
C.
gluon
A gluon is the elementary gauge boson in quantum chromodynamics that mediates the strong nuclear force between quarks and carries color charge.
-
D.
Symbol API
Symbol API is MXNet’s symbolic computation interface for defining, composing, and optimizing deep learning models as static computation graphs.
-
E.
Octavia API
Octavia API is the OpenStack load-balancing service interface that provides programmatic control over creating and managing scalable, high-availability load balancers.
- 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_69ca848f55e48190b3f67252571c3d45 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9c6d6dd48190a77c486337a58cb6 |
completed | April 1, 2026, 10:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d190f9bf78819093542adae997a668 |
completed | April 4, 2026, 10:30 p.m. |
Created at: March 30, 2026, 8:15 p.m.