Triple
T6790388
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bézier curve |
E155915
|
entity |
| Predicate | usedIn |
P98
|
FINISHED |
| Object | PostScript |
E30048
|
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: PostScript | Statement: [Bézier curve, usedIn, PostScript]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: PostScript Context triple: [Bézier curve, usedIn, PostScript]
-
A.
PostScript
chosen
PostScript is a page description and programming language widely used in desktop publishing and printing to precisely define the layout and appearance of text and graphics.
-
B.
PasteScript
PasteScript is a Python-based command-line tool that streamlines creating, managing, and deploying web application projects through reusable templates and scripts.
-
C.
Ghostscript
Ghostscript is a suite of software that interprets and renders PostScript and PDF files, widely used for document viewing, printing, and conversion.
-
D.
Postscript-1969
Postscript-1969 is Thomas S. Kuhn’s later-added reflective essay to *The Structure of Scientific Revolutions*, in which he clarifies and refines key concepts such as paradigms and incommensurability in response to critics.
-
E.
Adobe PageMaker
Adobe PageMaker was one of the first widely used desktop publishing applications, popular in the 1980s and 1990s for creating professional-quality printed documents such as brochures, newsletters, and books.
- 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_69c6881770fc8190972b2906390380f5 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d2acbfc0819081f2d6cebfb91765 |
completed | March 27, 2026, 6:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c74253f9b4819099057c730237c269 |
completed | March 28, 2026, 2:52 a.m. |
Created at: March 27, 2026, 2:15 p.m.