Triple
T2254984
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Surah Al-Qamar |
E49700
|
entity |
| Predicate | recurrentPhrase |
P32383
|
FINISHED |
| Object | فَكَيْفَ كَانَ عَذَابِي وَنُذُرِ |
—
|
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: فَكَيْفَ كَانَ عَذَابِي وَنُذُرِ | Statement: [Surah Al-Qamar, recurrentPhrase, فَكَيْفَ كَانَ عَذَابِي وَنُذُرِ]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: recurrentPhrase Context triple: [Surah Al-Qamar, recurrentPhrase, فَكَيْفَ كَانَ عَذَابِي وَنُذُرِ]
-
A.
usedPhrase
Indicates that one entity employed or expressed a particular phrase in speech, writing, or another form of communication.
-
B.
recurrence
Indicates that an event, condition, or state happens again or repeatedly over time, often after a period of absence or resolution.
-
C.
recurringLyric
chosen
Indicates that a particular lyric or line reappears multiple times within a song or musical piece.
-
D.
refrainWord
Indicates that one entity avoids using, mentioning, or expressing a particular word or term in relation to another entity or context.
-
E.
refrain
Indicates that an entity deliberately holds back from performing a particular action or behavior.
- 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_69a88aaa9250819095e127d0d77e8a32 |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc121af78819085b2e601d2f9bcdf |
completed | March 7, 2026, 6:09 a.m. |
| PD | Predicate disambiguation | batch_69abbdb34c148190b51e99f540f97204 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:47 p.m.