Triple
T25827759
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Al-Lahab |
E650579
|
entity |
| Predicate | openingWordsInArabic |
P114900
|
FINISHED |
| Object | تَبَّتْ يَدَا أَبِي لَهَبٍ وَتَبَّ |
—
|
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: تَبَّتْ يَدَا أَبِي لَهَبٍ وَتَبَّ | Statement: [Al-Lahab, openingWordsInArabic, تَبَّتْ يَدَا أَبِي لَهَبٍ وَتَبَّ]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: openingWordsInArabic Context triple: [Al-Lahab, openingWordsInArabic, تَبَّتْ يَدَا أَبِي لَهَبٍ وَتَبَّ]
-
A.
hasOpeningWordsArabic
chosen
Indicates that an entity (such as a text, document, or work) has specific opening words expressed in the Arabic language.
-
B.
openingWordsHebrew
Indicates that the specified words are the opening (initial) words of a text or passage in Hebrew.
-
C.
verseTextArabic
Indicates the Arabic-language text content associated with a specific verse in a scriptural or poetic work.
-
D.
revealedInArabicOrder
Indicates that something was disclosed or made known following the original sequence in which it was revealed in Arabic.
-
E.
meaningInArabicRelatedForm
Indicates that one entity expresses the meaning of another entity in Arabic through a related or derived linguistic form.
- 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_69e7ab37438081908f1ccf6284839520 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f603bb02288190b40cedbed5b9651d |
completed | May 2, 2026, 2:01 p.m. |
| PD | Predicate disambiguation | batch_69f602d07590819085ac34b189613104 |
completed | May 2, 2026, 1:57 p.m. |
Created at: April 22, 2026, 7:37 a.m.