Triple
T15577678
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | سورة لهب |
E374409
|
entity |
| Predicate | تتضمن لفظا |
P24842
|
FINISHED |
| Object | مَا أَغْنَىٰ عَنْهُ مَالُهُ وَمَا كَسَبَ |
—
|
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: مَا أَغْنَىٰ عَنْهُ مَالُهُ وَمَا كَسَبَ | Statement: [سورة لهب, تتضمن لفظا, مَا أَغْنَىٰ عَنْهُ مَالُهُ وَمَا كَسَبَ]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: تتضمن لفظا Context triple: [سورة لهب, تتضمن لفظا, مَا أَغْنَىٰ عَنْهُ مَالُهُ وَمَا كَسَبَ]
-
A.
includesSaying
chosen
Indicates that one entity (such as a text, speech, or communication) contains or incorporates a particular saying, phrase, or quoted expression.
-
B.
sentencesIncluded
Indicates that one or more sentences are contained within, or form part of, a larger text, document, or collection.
-
C.
spellingIncludes
Indicates that the spelling of one entity contains, as a substring or component, the spelling of another entity.
-
D.
includesLanguage
Indicates that one entity contains, supports, or makes use of a specified language as part of its content, functionality, or representation.
-
E.
typicallyContain
Indicates that one entity is normally or commonly found within, included in, or held by another entity under usual circumstances.
- 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_69d85ccd575081908909b71a3f3e3a61 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e22c89081909b1ec0cd36a1ef45 |
completed | April 16, 2026, 2:49 a.m. |
| PD | Predicate disambiguation | batch_69deda817e9881909b0c66fc9056f7d5 |
completed | April 15, 2026, 12:23 a.m. |
Created at: April 10, 2026, 4:11 a.m.