Triple
T16906757
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Proto-Sinaitic letter ʿayin |
E424582
|
entity |
| Predicate | correspondsToInArabic |
P125165
|
FINISHED |
| Object | Arabic ʿayn (ع) |
—
|
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 ʿayn (ع) | Statement: [Proto-Sinaitic letter ʿayin, correspondsToInArabic, Arabic ʿayn (ع)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: correspondsToInArabic Context triple: [Proto-Sinaitic letter ʿayin, correspondsToInArabic, Arabic ʿayn (ع)]
-
A.
hasNameInArabic
Indicates that an entity is associated with a specific name expressed in the Arabic language.
-
B.
correspondsToEnglishLetter
Indicates that one entity is the English alphabet letter that matches, represents, or is equivalent to the other entity.
-
C.
verseTextArabic
Indicates the Arabic-language text content associated with a specific verse in a scriptural or poetic work.
-
D.
correspondsToLatinWord
Indicates that one element is the equivalent or matching term of another element in Latin.
-
E.
cognateInArabic
Indicates that a given term has a corresponding cognate form in Arabic that is historically or linguistically related in origin or structure.
- 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_69d889da3e8c8190a2b118f383f0beac |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e3ca39f9b08190b15106c6caf895ec |
completed | April 18, 2026, 6:15 p.m. |
| PD | Predicate disambiguation | batch_69e32b9489408190bcb2ede567ff5bf9 |
completed | April 18, 2026, 6:58 a.m. |
| PDg | Predicate description generation | batch_69e34fb7c8c8819086975b7955b7d8ef |
completed | April 18, 2026, 9:32 a.m. |
Created at: April 10, 2026, 5:30 a.m.