Triple
T12562134
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TeX Live |
E295375
|
entity |
| Predicate | includes |
P1393
|
FINISHED |
| Object | MetaPost |
E437480
|
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: MetaPost | Statement: [TeX Live, includes, MetaPost]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MetaPost Context triple: [TeX Live, includes, MetaPost]
-
A.
METAPOST
chosen
METAPOST is a programming language and system for creating vector graphics, especially technical illustrations, by producing PostScript output using a syntax similar to METAFONT.
-
B.
METAFONT
METAFONT is a font description and rasterization system created by Donald Knuth for designing and generating bitmap fonts, particularly for use with the TeX typesetting system.
-
C.
The METAFONTbook
The METAFONTbook is Donald Knuth’s comprehensive manual and reference guide to the METAFONT system for designing and programming digital typefaces.
-
D.
XeTeX
XeTeX is an extension of the TeX typesetting system that natively supports Unicode and modern font technologies like OpenType, enabling high-quality multilingual and typographically advanced document production.
-
E.
LaTeX
LaTeX is a widely used, high-quality typesetting system particularly popular in academia for producing technical and scientific documents with precise control over layout and mathematical notation.
- 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_69d6ad9cac2c81908e8a7bed82d1e21d |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d95494ae1c81908b9ee14b8ef92a65 |
completed | April 10, 2026, 7:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6558da7e0819086860bfaf394e2d8 |
completed | May 2, 2026, 7:50 p.m. |
Created at: April 8, 2026, 11:48 p.m.