Triple
T14313447
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | سورة التكاثر |
E354892
|
entity |
| Predicate | عدد حروفها التقريبي |
P7444
|
FINISHED |
| Object | 120 |
—
|
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: 120 | Statement: [سورة التكاثر, عدد حروفها التقريبي, 120]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: عدد حروفها التقريبي Context triple: [سورة التكاثر, عدد حروفها التقريبي, 120]
-
A.
hasApproximateNumberOfLetters
chosen
Indicates that an entity is associated with a number that roughly, but not exactly, corresponds to the count of letters it contains.
-
B.
lengthInArabicWordsApprox
Indicates that the approximate length of something is expressed in Arabic words.
-
C.
hasNumberOfLetters
Indicates a relationship where an entity is associated with the count of letters it contains.
-
D.
numberOfCharacters
Indicates the total count of individual characters present in a given text, string, or entity’s representation.
-
E.
lengthInWords
Indicates the number of words that make up the length of something, typically a text or expression.
- 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_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. |
Created at: April 10, 2026, 1:12 a.m.