Triple
T20083863
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eski Camii |
E500071
|
entity |
| Predicate | hasCalligraphyLanguage |
P138654
|
FINISHED |
| Object | Arabic |
—
|
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 | Statement: [Eski Camii, hasCalligraphyLanguage, Arabic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCalligraphyLanguage Context triple: [Eski Camii, hasCalligraphyLanguage, Arabic]
-
A.
hasCalligraphy
Indicates that an entity possesses or is associated with calligraphy, such as having calligraphic writing, decoration, or stylistic features.
-
B.
hasWritingSystemForMajorLanguage
Indicates that there exists a writing system used to represent a major language associated with the given entity.
-
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.
hasTypography
Indicates that one entity uses, is associated with, or is characterized by a particular typographic style, font, or text layout.
-
E.
hasWritingDirection
Indicates the direction in which writing or text is read or written for a given script, language, or text system.
- F. None of above. chosen
Provenance (4 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_69da627770948190997f486f9a2e370f |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6655a2d2c81908a6b8fd2f209a825 |
completed | April 20, 2026, 5:41 p.m. |
| PD | Predicate disambiguation | batch_69e54cf369b88190931532420517dac7 |
completed | April 19, 2026, 9:45 p.m. |
| PDg | Predicate description generation | batch_69e54fc20888819083c9118a09d0d2dc |
completed | April 19, 2026, 9:57 p.m. |
Created at: April 11, 2026, 3:41 p.m.