Triple
T4276991
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jupyter Notebook |
E97066
|
entity |
| Predicate | originatedFrom |
P409
|
FINISHED |
| Object | IPython Notebook |
E97066
|
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: IPython Notebook | Statement: [Jupyter Notebook, originatedFrom, IPython Notebook]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: IPython Notebook Context triple: [Jupyter Notebook, originatedFrom, IPython Notebook]
-
A.
Jupyter Notebook
chosen
Jupyter Notebook is an open-source web-based interactive computing environment that allows users to create and share documents containing live code, equations, visualizations, and narrative text.
-
B.
JupyterLab
JupyterLab is a web-based interactive development environment for working with Jupyter notebooks, code, and data.
-
C.
Datalore
Datalore is JetBrains’ collaborative data science and analytics platform that combines notebooks, computation, and team features for working with code and data in the cloud.
-
D.
IronPython
IronPython is an implementation of the Python programming language that runs on the .NET framework, allowing Python code to interoperate seamlessly with .NET libraries and applications.
-
E.
Streamlit
Streamlit is an open-source Python framework that lets developers quickly build and share interactive web apps for data science and machine learning.
- 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_69b34544be3c819084d1ab82d29f90c5 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3501ef1388190b0c968b069014a59 |
completed | March 12, 2026, 11:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5b7b3b52c8190ae7c05448faf5558 |
completed | March 14, 2026, 7:32 p.m. |
Created at: March 12, 2026, 11:07 p.m.