Triple
T14075263
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Morning Brightness |
E338713
|
entity |
| Predicate | hasArabicOpening |
P6450
|
FINISHED |
| Object | وَالضُّحَى |
—
|
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: وَالضُّحَى | Statement: [The Morning Brightness, hasArabicOpening, وَالضُّحَى]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasArabicOpening Context triple: [The Morning Brightness, hasArabicOpening, وَالضُّحَى]
-
A.
hasNameInArabic
chosen
Indicates that an entity is associated with a specific name expressed in the Arabic language.
-
B.
revealedInArabicOrder
Indicates that something was disclosed or made known following the original sequence in which it was revealed in Arabic.
-
C.
hasGivenNameFormInArabic
Indicates that an entity has a specific given-name form expressed in the Arabic language.
-
D.
hasArabicNumeral
Indicates that an entity is associated with, represented by, or expressed using an Arabic numeral.
-
E.
keyOfOpening
Indicates that one entity functions as the key used to open another entity (such as a lock, door, or container).
- 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_69d81c687b0c819087fd9ed4198403f8 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de5c5cdd288190914e1d57321b3554 |
completed | April 14, 2026, 3:25 p.m. |
| PD | Predicate disambiguation | batch_69de05b0e6c88190a819eeba0028981f |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:21 p.m.