Triple
T15741612
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arabic Yaʼ |
E381614
|
entity |
| Predicate | usedAsMaterLectionis |
P44423
|
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: [Arabic Yaʼ, usedAsMaterLectionis, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedAsMaterLectionis Context triple: [Arabic Yaʼ, usedAsMaterLectionis, yes]
-
A.
isMaterLectionis
chosen
Indicates that a letter functions as a mater lectionis, i.e., it represents a vowel sound rather than serving as a consonant.
-
B.
usedInLiturgy
Indicates that something is employed or incorporated as part of a formal religious liturgy or worship service.
-
C.
hasLiturgicalReading
Indicates that a religious service, observance, or liturgical event includes or is associated with a specific prescribed reading from scripture or other sacred text.
-
D.
usesAlsoLiturgy
Indicates that an entity additionally employs or follows a particular liturgy alongside its primary or other liturgical practices.
-
E.
liturgicalText
Indicates that one entity is a liturgical or ritual text used in the religious or ceremonial practices associated with another entity.
- 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_69d86d9cdb648190bf3171be0bd7d872 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e0b4d6b5788190883746ee82c799f5 |
completed | April 16, 2026, 10:07 a.m. |
| PD | Predicate disambiguation | batch_69e0052c6208819098165d61d378d13b |
completed | April 15, 2026, 9:37 p.m. |
Created at: April 10, 2026, 4:46 a.m.