Triple
T21170057
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prime Reading |
E521666
|
entity |
| Predicate | platform |
P1292
|
FINISHED |
| Object | Kindle |
—
|
NE NERFINISHED |
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: Kindle | Statement: [Prime Reading, platform, Kindle]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kindle Context triple: [Prime Reading, platform, Kindle]
-
A.
Kindle
chosen
Kindle is Amazon’s line of portable e-readers designed primarily for reading digital books and other electronic publications.
-
B.
Kindle Cloud Reader
Kindle Cloud Reader is a web-based application by Amazon that lets users read and manage their Kindle ebooks directly in a browser without needing a dedicated device or app.
-
C.
Kobo e-readers
Kobo e-readers are a line of digital reading devices known for their wide format support, integration with public libraries, and openness compared to many competing platforms.
-
D.
Kobo
Kobo is a town in the Wollo region of northern Ethiopia, known as an agricultural center situated along key transport routes.
-
E.
Nook e-reader
The Nook e-reader is Barnes & Noble’s line of electronic reading devices designed for purchasing, downloading, and reading digital books and other publications.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b50e30748190b186824a206d39b9 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e72711be9481909f16107b71d3500a |
completed | April 21, 2026, 7:28 a.m. |
Created at: April 16, 2026, 3 p.m.