Triple
T22444244
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dojo |
E554825
|
entity |
| Predicate | hasComponent |
P35
|
FINISHED |
| Object | dojo.data |
—
|
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: dojo.data | Statement: [Dojo, hasComponent, dojo.data]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: dojo.data Context triple: [Dojo, hasComponent, dojo.data]
-
A.
Object Data Manager
Object Data Manager is a system component responsible for storing, organizing, and managing configuration and other structured data for applications or services.
-
B.
DataSet API
DataSet API is Apache Flink’s now-legacy batch processing API for defining and executing scalable, distributed data transformations.
-
C.
Dojo Toolkit
chosen
Dojo Toolkit is an open-source JavaScript framework designed to simplify building rich, interactive web applications with features for UI components, data handling, and cross-browser compatibility.
-
D.
ADF Data Controls
ADF Data Controls are a key Oracle ADF framework feature that expose business services and data models in a declarative, reusable way for rapid UI development.
-
E.
Core Data
Core Data is Apple’s object graph and persistence framework used in macOS and iOS apps to manage and store model layer data.
- 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_69e11e5113208190ab58c6b595f9d1d0 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15ae517208190924a7968723f55ef |
completed | April 29, 2026, 1:12 a.m. |
Created at: April 16, 2026, 8:47 p.m.