Triple
T4683346
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dash |
E103855
|
entity |
| Predicate | compatibleWith |
P203
|
FINISHED |
| Object | Plotly Express |
E17664
|
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: Plotly Express | Statement: [Dash, compatibleWith, Plotly Express]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Plotly Express Context triple: [Dash, compatibleWith, Plotly Express]
-
A.
Plotly
chosen
Plotly is an interactive, open-source graphing and data visualization library widely used in Python for creating rich, web-based charts and dashboards.
-
B.
Seaborn
Seaborn is a Python data visualization library built on top of Matplotlib that provides a high-level interface for creating attractive and informative statistical graphics.
-
C.
Seaborn
Seaborn is a masculine given name of English origin, historically used in colonial America and associated with individuals such as Seaborn Cotton.
-
D.
Matplotlib
Matplotlib is a widely used Python plotting library for creating static, animated, and interactive visualizations.
-
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_69bd43debbf08190b4bc372e286ec234 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd638130a08190876c5829c0488758 |
completed | March 20, 2026, 3:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be03b07664819097d959fde1b0585b |
completed | March 21, 2026, 2:34 a.m. |
Created at: March 20, 2026, 1:16 p.m.