Triple
T18015965
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NumFOCUS |
E430998
|
entity |
| Predicate | supportsProject |
P12986
|
FINISHED |
| Object | Conda |
—
|
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: Conda | Statement: [NumFOCUS, supportsProject, Conda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Conda Context triple: [NumFOCUS, supportsProject, Conda]
-
A.
Conda
chosen
Conda is an open-source package and environment management system widely used in the Python and data science ecosystem to install, manage, and isolate software dependencies across platforms.
-
B.
Conda
Conda is a municipality located in Cuanza Sul Province in west-central Angola.
-
C.
Anaconda installer
The Anaconda installer is a graphical and text-based system installation program primarily used by Fedora and other Red Hat–related Linux distributions to guide users through setting up their operating system.
-
D.
Pipenv
Pipenv is a Python packaging and dependency management tool that combines virtual environment handling with a Pipfile-based workflow to simplify and standardize project setup.
-
E.
Pythion
Pythion was an ancient city of Perrhaebia in northern Thessaly, Greece, likely known for its regional religious and strategic significance.
- 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_69d8b904530081908bf341d842464856 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4b523f588819097389e067dda7f23 |
completed | April 19, 2026, 10:57 a.m. |
Created at: April 10, 2026, 10:24 a.m.