Triple
T36001748
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | العرش |
E1041149
|
entity |
| Predicate | يميز_عن |
P159345
|
FINISHED |
| Object | الكرسي في التفسير السني الشائع |
—
|
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: الكرسي في التفسير السني الشائع | Statement: [العرش, يميز_عن, الكرسي في التفسير السني الشائع]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: يميز_عن Context triple: [العرش, يميز_عن, الكرسي في التفسير السني الشائع]
-
A.
يميز
chosen
Indicates that one entity distinguishes, differentiates, or sets something apart from something else.
-
B.
distinguishingTrait
Indicates that a particular characteristic or feature uniquely differentiates one entity from another.
-
C.
characterizedBy
Indicates that one entity possesses a defining quality, feature, or attribute expressed by another entity.
-
D.
distinguéDe
Indicates that one entity is distinguished from or set apart as different from another entity.
-
E.
spanCharacteristic
Indicates that one entity has a particular measurable or descriptive property that characterizes the extent, duration, or range of another entity or phenomenon.
- 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_69f76e2a02208190aedd1f9025a8b300 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7acaec1508190a38f2ac9cc5383e7 |
completed | May 3, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69f7ab75387c819091afc3c2128eb903 |
completed | May 3, 2026, 8:09 p.m. |
Created at: May 3, 2026, 4:07 p.m.