Triple
T26099345
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Great Mongol Shahnama |
E658352
|
entity |
| Predicate | originalNumberOfIllustrations |
P73649
|
FINISHED |
| Object | over 190 |
—
|
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: over 190 | Statement: [Great Mongol Shahnama, originalNumberOfIllustrations, over 190]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originalNumberOfIllustrations Context triple: [Great Mongol Shahnama, originalNumberOfIllustrations, over 190]
-
A.
numberOfIllustrations
chosen
Indicates the quantity of illustrations associated with or contained in an entity.
-
B.
hasIllustrations
Indicates that an entity includes or is accompanied by visual illustrations.
-
C.
hasIllustrationsBy
Indicates that one entity (such as a work or publication) includes illustrations that were created by another entity (the illustrator).
-
D.
hasColorIllustrations
Indicates that an entity contains or includes illustrations rendered in color.
-
E.
hasBlackAndWhiteIllustrations
Indicates that the subject contains or features illustrations rendered in black and white.
- 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_69ee5bc09c288190bc42a11972841383 |
completed | April 26, 2026, 6:38 p.m. |
| NER | Named-entity recognition | batch_69fb6fdc7eb081908ab8475efb38c430 |
completed | May 6, 2026, 4:44 p.m. |
| PD | Predicate disambiguation | batch_69fb5a986e588190b7a10892bd2ff44c |
completed | May 6, 2026, 3:13 p.m. |
Created at: April 26, 2026, 7:53 p.m.