Triple
T66761
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arabic |
E1330
|
entity |
| Predicate | hasCalligraphicTradition |
P958
|
FINISHED |
| Object | Arabic calligraphy |
—
|
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 calligraphy | Statement: [Arabic, hasCalligraphicTradition, Arabic calligraphy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCalligraphicTradition Context triple: [Arabic, hasCalligraphicTradition, Arabic calligraphy]
-
A.
hasWritingTraditionSince
Indicates that a writing tradition has been present or established for an entity starting from a specified point in time.
-
B.
hasCulturalSignificanceFor
chosen
Indicates that something holds particular cultural meaning, value, or importance for a specified group or community.
-
C.
culturalTradition
Indicates a relationship where certain practices, beliefs, or customs are recognized as part of a shared cultural heritage passed down within a group or society.
-
D.
literaryTradition
Indicates a relationship where a work, practice, or expression belongs to, arises from, or participates in a particular established body of literary customs, styles, or conventions.
-
E.
isMostWidelyUsedWritingSystem
Indicates that the subject writing system is used by more people or in more contexts than any other writing system.
- 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_69a24ba4f760819081f6638a3c70538a |
completed | Feb. 28, 2026, 1:57 a.m. |
| NER | Named-entity recognition | batch_69a2509b5a088190bb9d2b650aeb8bca |
completed | Feb. 28, 2026, 2:19 a.m. |
| PD | Predicate disambiguation | batch_69a24ea749788190bc17865171ff909a |
completed | Feb. 28, 2026, 2:10 a.m. |
Created at: Feb. 28, 2026, 2:02 a.m.