Triple
T7398474
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kobo e-readers |
E170684
|
entity |
| Predicate | hasModel |
P2390
|
FINISHED |
| Object | Kobo Clara series |
E170684
|
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: Kobo Clara series | Statement: [Kobo e-readers, hasModel, Kobo Clara series]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kobo Clara series Context triple: [Kobo e-readers, hasModel, Kobo Clara series]
-
A.
Kobo e-readers
chosen
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.
-
B.
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.
-
C.
Onyx Boox e-readers
Onyx Boox e-readers are Android-based digital reading devices known for their versatile app support, stylus-enabled note-taking, and eye-friendly E Ink displays.
-
D.
Calibre
Calibre is a 2018 British thriller film about a hunting trip in the Scottish Highlands that goes disastrously wrong, starring Jack Lowden.
-
E.
Calibre
Calibre is an electronic design automation tool suite from Mentor Graphics widely used for physical verification and design rule checking in semiconductor chip design.
- 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_69c68a5f04188190ac266569c9280347 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f24c1c208190a3d11e816888760d |
completed | March 27, 2026, 9:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c81106c0788190a3740acf7bb4ab86 |
completed | March 28, 2026, 5:33 p.m. |
Created at: March 27, 2026, 3:09 p.m.