Triple
T12765003
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | سورة المطففين |
E305099
|
entity |
| Predicate | عدد حروفها |
P4429
|
FINISHED |
| Object | 730 تقريباً |
—
|
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: 730 تقريباً | Statement: [سورة المطففين, عدد حروفها, 730 تقريباً]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: عدد حروفها Context triple: [سورة المطففين, عدد حروفها, 730 تقريباً]
-
A.
hasNumberOfLetters
chosen
Indicates a relationship where an entity is associated with the count of letters it contains.
-
B.
numberOfCharacters
Indicates the total count of individual characters present in a given text, string, or entity’s representation.
-
C.
usesAdditionalLettersFrom
Indicates that one entity forms or derives its representation by incorporating extra letters taken from another entity beyond those originally present.
-
D.
hasLettersFor
Indicates that one entity possesses or contains written correspondence intended for another entity.
-
E.
عدد المقاطع
Indicates the number of segments or parts into which something is divided.
- 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_69d7bdf1fcd081909ffb0e0d6fa3a07d |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96df1ef148190af525532fcb0933b |
completed | April 10, 2026, 9:38 p.m. |
| PD | Predicate disambiguation | batch_69d96409739881909174ba005a986cb5 |
completed | April 10, 2026, 8:56 p.m. |
Created at: April 9, 2026, 5:28 p.m.