Triple
T31992298
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DjVu |
E816903
|
entity |
| Predicate | advantageOverPDF |
P173095
|
FINISHED |
| Object | smaller file size for scanned documents |
—
|
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: smaller file size for scanned documents | Statement: [DjVu, advantageOverPDF, smaller file size for scanned documents]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: advantageOverPDF Context triple: [DjVu, advantageOverPDF, smaller file size for scanned documents]
-
A.
advantageOverApps
Indicates that one entity possesses a benefit or superiority when compared to applications (apps).
-
B.
advantageOverHDD
Indicates that one entity possesses a benefit, superiority, or improvement when compared to a hard disk drive (HDD).
-
C.
digitalPublisher
Indicates the entity that is responsible for publishing the resource in a digital format.
-
D.
advantageOverCookies
Indicates a comparative relationship where one option, method, or entity is considered to have benefits or superiority when compared specifically to cookies.
-
E.
advantageOverCRT
Indicates that one entity possesses a benefit, superiority, or favorable quality when compared to CRT.
- 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_69f348f8002081909a3588758ba94afb |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6b3badf8481909377856a516a982b |
completed | May 3, 2026, 2:32 a.m. |
| PD | Predicate disambiguation | batch_69f6b151ad008190836c1bcdec503ce2 |
completed | May 3, 2026, 2:22 a.m. |
| PDg | Predicate description generation | batch_69f6b21da77081908c5c015c4606d344 |
completed | May 3, 2026, 2:25 a.m. |
Created at: May 1, 2026, 12:13 a.m.