Triple
T36946826
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yawm al-Jumu'ah |
E913935
|
entity |
| Predicate | specialHour |
P106818
|
FINISHED |
| Object | time when supplications are accepted |
—
|
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: time when supplications are accepted | Statement: [Yawm al-Jumu'ah, specialHour, time when supplications are accepted]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: specialHour Context triple: [Yawm al-Jumu'ah, specialHour, time when supplications are accepted]
-
A.
specialSeason
Indicates that an entity is associated with a particular season that is distinguished or treated differently from regular seasons (e.g., for events, offers, or conditions).
-
B.
isHolidaySpecialOf
Indicates that something is a special version, event, or offering specifically created for or associated with a particular holiday.
-
C.
peakHours
Indicates that an action, event, or condition occurs during the busiest or most heavily trafficked time period.
-
D.
hasTimeOfSpecialAttraction
chosen
Indicates a relationship where something is associated with a specific time period during which it has a heightened or special level of attraction.
-
E.
rushHourServicePattern
Indicates that a service operates according to a specific pattern or schedule that applies only during rush-hour or peak travel times.
- 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_69f76e8b28848190abd81fe7a7374910 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fd4129a8848190a5002150278ac689 |
completed | May 8, 2026, 1:49 a.m. |
| PD | Predicate disambiguation | batch_69fd3e0515ec8190937c7af71ebc3875 |
completed | May 8, 2026, 1:36 a.m. |
Created at: May 3, 2026, 4:13 p.m.