Triple
T12562052
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | XeTeX |
E295373
|
entity |
| Predicate | relatedTo |
P37
|
FINISHED |
| Object | LuaTeX |
E308572
|
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: LuaTeX | Statement: [XeTeX, relatedTo, LuaTeX]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: LuaTeX Context triple: [XeTeX, relatedTo, LuaTeX]
-
A.
LuaTeX
chosen
LuaTeX is an extended TeX-based typesetting engine that embeds the Lua scripting language to provide powerful programmability and advanced typographic features beyond traditional LaTeX workflows.
-
B.
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.
-
C.
pdfTeX
pdfTeX is an extended version of Knuth’s TeX engine that can directly generate PDF output and offers advanced typographic and microtypographic features.
-
D.
LaTeX3
LaTeX3 is the next-generation, experimental programming layer and macro system for LaTeX, designed to provide a more consistent, modular, and extensible foundation for document preparation.
-
E.
upTeX
upTeX is a Japanese-enabled TeX engine that extends pTeX with full Unicode support for typesetting multilingual documents, especially those containing Japanese text.
- 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.