Triple
T6718402
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maghrib |
E153331
|
entity |
| Predicate | numberOfObligatoryRakats |
P28128
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [Maghrib, numberOfObligatoryRakats, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfObligatoryRakats Context triple: [Maghrib, numberOfObligatoryRakats, 3]
-
A.
numberOfRakats
chosen
Indicates the specific count of prayer units (rakats) associated with a given prayer or ritual act.
-
B.
includesOptionalRakats
Indicates that the relationship or action involves the inclusion of optional rakats (units of prayer) as part of a broader prayer or ritual sequence.
-
C.
optionalRakatsType
Indicates that a particular type or number of rakats (units of Islamic prayer) is optionally associated with or applicable to an action, event, or prayer.
-
D.
numberOfImams
Indicates the count of distinct imams associated with or relevant to a given entity or context.
-
E.
recitationInFirstRakats
Indicates that the specified recitation occurs during the first rak‘ah (unit) of the prayer.
- 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_69c68809b4608190a2509ddb5ab87f05 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d135d27c819088c45839ad0e7bab |
completed | March 27, 2026, 6:49 p.m. |
| PD | Predicate disambiguation | batch_69c6d08c5d348190a29dee668c398e70 |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:07 p.m.