Triple
T5451930
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Apple Books |
E122389
|
entity |
| Predicate | formerName |
P65
|
FINISHED |
| Object | iBooks |
E122389
|
NE 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: iBooks | Statement: [Apple Books, formerName, iBooks]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: iBooks Context triple: [Apple Books, formerName, iBooks]
-
A.
Apple Books
chosen
Apple Books is Apple’s e-book and audiobook platform and reading app, available across its devices for purchasing, organizing, and enjoying digital books and audio content.
-
B.
Google Play Books
Google Play Books is a digital distribution service and e-book/audiobook reader platform from Google that lets users purchase, download, and read or listen to books across devices.
-
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.
Kindle
Kindle is Amazon’s line of portable e-readers designed primarily for reading digital books and other electronic publications.
-
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 (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_69bd46424248819085282ddf50a565f3 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd91dfec248190af6f9c793a99c34c |
completed | March 20, 2026, 6:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf413d25008190b100c8297d6063b1 |
completed | March 22, 2026, 1:09 a.m. |
Created at: March 20, 2026, 2:08 p.m.