Triple
T7058827
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | عبد المطلب |
E164162
|
entity |
| Predicate | الموقف_في_حادثة_الفيل |
P74795
|
FINISHED |
| Object | دعا الله أن يحمي البيت الحرام من أبرهة وجيش الفيل |
—
|
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: دعا الله أن يحمي البيت الحرام من أبرهة وجيش الفيل | Statement: [عبد المطلب, الموقف_في_حادثة_الفيل, دعا الله أن يحمي البيت الحرام من أبرهة وجيش الفيل]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: الموقف_في_حادثة_الفيل Context triple: [عبد المطلب, الموقف_في_حادثة_الفيل, دعا الله أن يحمي البيت الحرام من أبرهة وجيش الفيل]
-
A.
lionArmedAndLangued
Indicates that a lion is depicted with its claws and tongue emphasized, typically by being shown and colored distinctly.
-
B.
involvedInAccident
Indicates that an entity participated in, was affected by, or was otherwise a party to a specific accident or collision event.
-
C.
resultOfAccident
Indicates that something exists or occurs as a consequence or outcome of an accident.
-
D.
fromNoseCame
Indicates that something originated from or was expelled out of a nose.
-
E.
allegedRescueEvent
Indicates that an event is claimed or reported to be a rescue, but its occurrence or nature is not confirmed as factual.
- F. None of above. chosen
Provenance (4 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_69c68861678881909961ddf4d779f750 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6e4a3c36c819080942c59f1830ae8 |
completed | March 27, 2026, 8:12 p.m. |
| PD | Predicate disambiguation | batch_69c6e1bdc1f08190975fcdbbb1854d1e |
completed | March 27, 2026, 7:59 p.m. |
| PDg | Predicate description generation | batch_69c6e4a15b088190bee9a23e94aaac53 |
completed | March 27, 2026, 8:12 p.m. |
Created at: March 27, 2026, 2:38 p.m.