Triple
T148169
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tableau |
E3373
|
entity |
| Predicate | programmingLanguage |
P1592
|
FINISHED |
| Object | Python |
E3372
|
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: Python | Statement: [Tableau, programmingLanguage, Python]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Python Context triple: [Tableau, programmingLanguage, Python]
-
A.
Python
chosen
Python is a high-level, versatile programming language widely used for data analysis, machine learning, web development, and automation.
-
B.
PyPy
PyPy is a high-performance alternative Python interpreter featuring a Just-In-Time (JIT) compiler designed to significantly speed up the execution of Python programs.
-
C.
Jython
Jython is an implementation of the Python programming language that runs on the Java platform and allows seamless integration with Java code and libraries.
-
D.
Python Software Foundation
The Python Software Foundation is a non-profit organization that manages the development, licensing, and community support of the Python programming language.
-
E.
MicroPython
MicroPython is a lean and efficient reimplementation of the Python 3 language designed to run on microcontrollers and other resource-constrained embedded systems.
- 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_69a252868de4819080e21c9938bfe8b6 |
completed | Feb. 28, 2026, 2:27 a.m. |
| NER | Named-entity recognition | batch_69a257ecb6f48190992c4c8ca908a81c |
completed | Feb. 28, 2026, 2:50 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a2c52df3b48190960c53fd872ff897 |
completed | Feb. 28, 2026, 10:36 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.