Triple
T2814358
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Apple Magic Mouse |
E54246
|
entity |
| Predicate | usedWith |
P4791
|
FINISHED |
| Object | MacBook |
E42442
|
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: MacBook | Statement: [Apple Magic Mouse, usedWith, MacBook]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MacBook Context triple: [Apple Magic Mouse, usedWith, MacBook]
-
A.
MacBook
chosen
MacBook is Apple’s line of macOS-based laptop computers known for their sleek design, high-resolution displays, and tight hardware–software integration.
-
B.
MacBook Pro
The MacBook Pro is Apple’s high-performance line of professional-grade laptop computers known for their powerful hardware, premium design, and macOS operating system.
-
C.
Mac mini
The Mac mini is a compact desktop computer designed by Apple that offers full macOS functionality in a small, versatile form factor suitable for both consumer and professional use.
-
D.
iMac
The iMac is Apple’s all-in-one desktop computer line known for integrating powerful hardware with a slim, minimalist display-focused design.
-
E.
iBook
The iBook was Apple’s line of consumer-oriented, portable Macintosh laptops designed for education and everyday use in the late 1990s and early 2000s.
- 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_69ab49de0af08190b3da69683be1e728 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abde4ba34c819085a336498fc326b0 |
completed | March 7, 2026, 8:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afce9f964081909e422aaf1f026dbb |
completed | March 10, 2026, 7:56 a.m. |
Created at: March 6, 2026, 9:59 p.m.