Triple
T28711731
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arabic Presentation Forms-A |
E729847
|
entity |
| Predicate | containsCompatibilityCharacters |
P195269
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Arabic Presentation Forms-A, containsCompatibilityCharacters, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsCompatibilityCharacters Context triple: [Arabic Presentation Forms-A, containsCompatibilityCharacters, true]
-
A.
hasNoConventionalCharacters
Indicates that the entity contains no standard alphanumeric or commonly used written characters.
-
B.
hasLanguageCharacter
Indicates that an entity uses, contains, or is associated with a specific written or symbolic character from a language.
-
C.
hasUnicode
Indicates that an entity is associated with, represented by, or encoded using a specific Unicode character or sequence.
-
D.
containsCharacter
Indicates that one entity includes a specific character as part of its content or composition.
-
E.
characterCoverage
Indicates that one entity provides or includes sufficient representation or support for the characters (e.g., glyphs, symbols, or scripts) required or used by another entity.
- 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_69f043e7d5a4819094b18aca10b1e024 |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_69fdb45537288190b6791078d4a6899f |
completed | May 8, 2026, 10 a.m. |
| PD | Predicate disambiguation | batch_69fdb39ad96481908376d7def9fafc13 |
completed | May 8, 2026, 9:57 a.m. |
| PDg | Predicate description generation | batch_69fdb4544b548190b8971f8055d48caa |
completed | May 8, 2026, 10 a.m. |
Created at: April 28, 2026, 5:48 a.m.