Triple
T4278023
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | pip |
E97086
|
entity |
| Predicate | hasSubcommand |
P22505
|
FINISHED |
| Object | pip config |
E97086
|
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: pip config | Statement: [pip, hasSubcommand, pip config]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: pip config Context triple: [pip, hasSubcommand, pip config]
-
A.
pip
chosen
pip is the standard command-line package manager for Python, used to install and manage software packages from the Python Package Index (PyPI) and other repositories.
-
B.
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.
-
C.
Python Package Index
The Python Package Index (PyPI) is the central online repository where developers publish and download open-source Python software packages.
-
D.
setuptools
setuptools is a widely used Python library for packaging, distributing, and installing Python projects and their dependencies.
-
E.
Python Packaging Authority
The Python Packaging Authority is a working group that oversees and develops key tools, standards, and infrastructure for packaging and distributing Python software.
- 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_69b5b7b708b481908c1683741f84ee55 |
completed | March 14, 2026, 7:32 p.m. |
Created at: March 12, 2026, 11:07 p.m.