Triple
T38160405
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zapfino Arabic |
E953000
|
entity |
| Predicate | supportsDiscretionaryLigatures |
P190168
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Zapfino Arabic, supportsDiscretionaryLigatures, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsDiscretionaryLigatures Context triple: [Zapfino Arabic, supportsDiscretionaryLigatures, yes]
-
A.
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.
-
B.
usesOpenTypeFeatures
chosen
Indicates that one entity employs or supports OpenType typographic features in relation to another entity or context.
-
C.
hasCursiveJoining
Indicates that one written character is connected to another through cursive-style joining.
-
D.
hasCalligraphyLanguage
Indicates that an entity’s calligraphy is written in, or associated with, a particular language.
-
E.
hasCalligraphy
Indicates that an entity possesses or is associated with calligraphy, such as having calligraphic writing, decoration, or stylistic features.
- 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_6a037df1223c8190a5d61e4f8e6fd613 |
completed | May 12, 2026, 7:22 p.m. |
| PD | Predicate disambiguation | batch_6a037a1ad6c48190bfe35d350c1b4751 |
completed | May 12, 2026, 7:06 p.m. |
Created at: May 3, 2026, 4:21 p.m.