Triple
T10825793
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | reStructuredText |
E255494
|
entity |
| Predicate | commonlyUsedWith |
P3100
|
FINISHED |
| Object | Docutils |
E888272
|
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: Docutils | Statement: [reStructuredText, commonlyUsedWith, Docutils]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Docutils Context triple: [reStructuredText, commonlyUsedWith, Docutils]
-
A.
Docutils
chosen
Docutils is an open-source text processing system for converting reStructuredText documents into formats such as HTML, LaTeX, and XML.
-
B.
Docutils project
The Docutils project is an open-source text processing system for converting lightweight markup documents, especially those written in reStructuredText, into formats such as HTML, LaTeX, and XML.
-
C.
reStructuredText
reStructuredText is a lightweight, plaintext markup language commonly used in the Python ecosystem for documentation, including PEPs and Sphinx-based docs.
-
D.
Sphinx documentation
Sphinx documentation is the official and user-generated reference material that explains how to use the Sphinx tool to create, configure, and build structured software documentation.
-
E.
DocBook
DocBook is a semantic markup language, originally based on SGML and now commonly used in XML form, designed for authoring and publishing technical documentation and books in a platform-independent way.
- 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_69d6aa8081448190a9324184f2bd1c26 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d734d0389c819090a892693c4046ed |
completed | April 9, 2026, 5:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69dff7c45f288190a5235b5d7000a32c |
completed | April 15, 2026, 8:40 p.m. |
Created at: April 8, 2026, 9:19 p.m.