Triple
T24899230
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | لوط |
E623528
|
entity |
| Predicate | اشتهر_بقصة |
P157456
|
FINISHED |
| Object | نزول_الحجارة_على_قومه |
—
|
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: نزول_الحجارة_على_قومه | Statement: [لوط, اشتهر_بقصة, نزول_الحجارة_على_قومه]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: اشتهر_بقصة Context triple: [لوط, اشتهر_بقصة, نزول_الحجارة_على_قومه]
-
A.
اشتهر_بقصة
chosen
Indicates that someone or something became well-known or famous specifically because of a particular story.
-
B.
شهرت اصلی
Indicates a primary or most notable form of fame or recognition associated with an entity.
-
C.
شرحه
Indicates that one entity explains, interprets, or clarifies something to another entity.
-
D.
حكم تلاوتها
Indicates the ruling or legal judgment regarding the recitation of something (e.g., whether its recitation is obligatory, recommended, permissible, disliked, or forbidden).
-
E.
appearsInShortStoryBy
Indicates that one entity is a character, element, or subject that appears within a short story authored by another entity.
- 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_69e2fac797cc8190b30d77f4121099ac |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f453035f508190be83a3d521723acf |
completed | May 1, 2026, 7:15 a.m. |
| PD | Predicate disambiguation | batch_69f44d77f6e88190a4643ab2cbef567b |
completed | May 1, 2026, 6:51 a.m. |
Created at: April 18, 2026, 5:26 a.m.