Triple
T816673
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Plotly |
E17664
|
entity |
| Predicate | hasComponent |
P35
|
FINISHED |
| Object |
plotly.js
plotly.js is an open-source JavaScript graphing library for creating interactive, publication-quality data visualizations in web applications.
|
E17664
|
NE FINISHED |
How this triple was built (4 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.js | Statement: [Plotly, hasComponent, plotly.js]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: plotly.js Context triple: [Plotly, hasComponent, plotly.js]
-
A.
Plotly
Plotly is an interactive, open-source graphing and data visualization library widely used in Python for creating rich, web-based charts and dashboards.
-
B.
Power View
Power View is an interactive data visualization and reporting tool from Microsoft that enables users to create dynamic, presentation-ready dashboards and reports.
-
C.
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.
-
D.
Streamlit
Streamlit is an open-source Python framework that lets developers quickly build and share interactive web apps for data science and machine learning.
-
E.
Matplotlib
Matplotlib is a widely used Python plotting library for creating static, animated, and interactive visualizations.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: plotly.js Triple: [Plotly, hasComponent, plotly.js]
Generated description
plotly.js is an open-source JavaScript graphing library for creating interactive, publication-quality data visualizations in web applications.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: plotly.js Target entity description: plotly.js is an open-source JavaScript graphing library for creating interactive, publication-quality data visualizations in web applications.
-
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.
Power View
Power View is an interactive data visualization and reporting tool from Microsoft that enables users to create dynamic, presentation-ready dashboards and reports.
-
C.
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.
-
D.
Streamlit
Streamlit is an open-source Python framework that lets developers quickly build and share interactive web apps for data science and machine learning.
-
E.
Matplotlib
Matplotlib is a widely used Python plotting library for creating static, animated, and interactive visualizations.
- F. None of above.
Provenance (5 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_69a4937bcaac8190a322524ac6f45a5a |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4ab621d2c819083f10bff4f66c482 |
completed | March 1, 2026, 9:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a7928f8a808190aaf5f2a2f3ee676f |
completed | March 4, 2026, 2:01 a.m. |
| NEDg | Description generation | batch_69a7976b7334819082bb9f40601c1092 |
completed | March 4, 2026, 2:22 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a79b206a5481908591ee9e1d6b3fdd |
completed | March 4, 2026, 2:38 a.m. |
Created at: March 1, 2026, 7:38 p.m.