Triple
T14470101
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Destruction of the Army of the Elephant |
E358815
|
entity |
| Predicate | associatedWithQuranicTerm |
P71465
|
FINISHED |
| Object | asf ma’kul |
—
|
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: asf ma’kul | Statement: [Destruction of the Army of the Elephant, associatedWithQuranicTerm, asf ma’kul]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithQuranicTerm Context triple: [Destruction of the Army of the Elephant, associatedWithQuranicTerm, asf ma’kul]
-
A.
groupedWithInQuran
Indicates that two or more entities are mentioned together or treated as a unit within the same grouping or context in the Quran.
-
B.
quranicOppositeTerm
Indicates that one term is presented in the Quran as the conceptual or semantic opposite of another term.
-
C.
quranicPhrase
chosen
Indicates that one entity is a phrase or expression that appears in, or is directly derived from, the Quran.
-
D.
hasQuranicDescription
Indicates that there exists a description or characterization of the subject that is explicitly given or referenced in the Quran.
-
E.
isAssociatedWithReligiousText
Indicates a relationship where an entity is connected or linked in some way to a religious text, such as being based on, derived from, or directly related to it.
- 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_69d827966698819082e140837737501d |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de91f969788190a5114f92d7159aae |
completed | April 14, 2026, 7:14 p.m. |
| PD | Predicate disambiguation | batch_69de5c42bd3c81909a62acf30cc24d1e |
completed | April 14, 2026, 3:24 p.m. |
Created at: April 10, 2026, 1:20 a.m.