Triple
T18052148
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sphinx |
E431947
|
entity |
| Predicate | supportsInputFormat |
P8463
|
FINISHED |
| Object | reStructuredText |
—
|
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: reStructuredText | Statement: [Sphinx, supportsInputFormat, reStructuredText]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: reStructuredText Context triple: [Sphinx, supportsInputFormat, reStructuredText]
-
A.
reStructuredText
chosen
reStructuredText is a lightweight, plaintext markup language commonly used in the Python ecosystem for documentation, including PEPs and Sphinx-based docs.
-
B.
Docutils
Docutils is an open-source text processing system for converting reStructuredText documents into formats such as HTML, LaTeX, and XML.
-
C.
MultiMarkdown
MultiMarkdown is an extended version of the Markdown markup language that adds features like tables, footnotes, citations, and document metadata for more complex publishing needs.
-
D.
Markdown
Markdown is a lightweight markup language that uses plain-text formatting syntax to create structured documents, most commonly used for README files, documentation, and web content.
-
E.
Read the Docs
Read the Docs is an open-source documentation hosting platform that automatically builds, version-manages, and serves technical docs for software projects.
- 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_69d8b906482481908183315b9ecf9994 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4c0fe4f1881908fa8485cb3ccfa44 |
completed | April 19, 2026, 11:48 a.m. |
Created at: April 10, 2026, 10:25 a.m.