Triple
T14313446
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | سورة التكاثر |
E354892
|
entity |
| Predicate | عدد كلماتها التقريبي |
P113736
|
FINISHED |
| Object | 28 |
—
|
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: 28 | Statement: [سورة التكاثر, عدد كلماتها التقريبي, 28]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: عدد كلماتها التقريبي Context triple: [سورة التكاثر, عدد كلماتها التقريبي, 28]
-
A.
عدد المقاطع
Indicates the number of segments or parts into which something is divided.
-
B.
لغة السورة
Indicates the language in which a given surah (chapter of the Qur’an) is expressed or written.
-
C.
تعداد باب
Indicates a relationship where the predicate specifies the number of doors that something has.
-
D.
التأثير
Indicates a relationship where one entity produces a change or has an influence on another entity or its state.
-
E.
hasApproximateNumberOfLetters
Indicates that an entity is associated with a number that roughly, but not exactly, corresponds to the count of letters it contains.
- F. None of above. chosen
Provenance (4 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_69d8278ed42c8190b9f882dcce611347 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de85b49e5481909b9ffab2d922e284 |
completed | April 14, 2026, 6:21 p.m. |
| PD | Predicate disambiguation | batch_69de2a8f81f08190af737e1654847aa6 |
completed | April 14, 2026, 11:52 a.m. |
| PDg | Predicate description generation | batch_69de2e07d1f88190bdcd20967e484718 |
completed | April 14, 2026, 12:07 p.m. |
Created at: April 10, 2026, 1:12 a.m.