Triple
T38160287
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Palatino Arabic |
E952996
|
entity |
| Predicate | hasGlyphSet |
P84314
|
FINISHED |
| Object | Arabic letters |
—
|
LITERAL 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: Arabic letters | Statement: [Palatino Arabic, hasGlyphSet, Arabic letters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGlyphSet Context triple: [Palatino Arabic, hasGlyphSet, Arabic letters]
-
A.
hasGlyphsFor
chosen
Indicates that one entity provides or contains the necessary glyphs or visual symbols to represent another entity.
-
B.
hasGlyphRepertoireSize
Indicates the number of distinct glyphs included in an entity’s glyph repertoire.
-
C.
hasLigatures
Indicates that one writing system, font, or text includes combined character forms (ligatures) that join two or more individual glyphs into a single symbol.
-
D.
hasCalligraphy
Indicates that an entity possesses or is associated with calligraphy, such as having calligraphic writing, decoration, or stylistic features.
-
E.
hasTypography
Indicates that one entity uses, is associated with, or is characterized by a particular typographic style, font, or text layout.
- F. None of above.
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_69f76f0b93c48190a117319ab3a9f282 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fcc42cbac48190b8d3e4c9ce140838 |
completed | May 7, 2026, 4:56 p.m. |
| PD | Predicate disambiguation | batch_69fcb0fc69c88190800453eb57a7e62c |
completed | May 7, 2026, 3:34 p.m. |
Created at: May 3, 2026, 4:21 p.m.