Triple
T13718616
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Epiphany |
E328966
|
entity |
| Predicate | hasTrack |
P3284
|
FINISHED |
| Object | Time Machine |
E835121
|
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: Time Machine | Statement: [Epiphany, hasTrack, Time Machine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Time Machine Context triple: [Epiphany, hasTrack, Time Machine]
-
A.
Time Machine
chosen
"Time Machine" is a pop-influenced song by American singer-songwriter Ingrid Michaelson, known for its upbeat sound and introspective lyrics about change and self-reflection.
-
B.
Time Machine (Mac OS X feature)
Time Machine is macOS’s built-in automatic backup system that regularly saves versions of your files and allows easy restoration of data from different points in time.
-
C.
The Finder
The Finder is a film featuring Australian actor Robert Mammone in a prominent role.
-
D.
FileVault
FileVault is Apple’s built-in full-disk encryption system for macOS that protects data by encrypting the contents of a Mac’s startup disk.
-
E.
OS X Mavericks
OS X Mavericks is a version of Apple's Mac operating system released in 2013 that focused on performance improvements, power efficiency, and tighter integration with iCloud and other Apple services.
- 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_69d80770b9bc81909f70c8c317d53cff |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dd439a121c81908cae964e7756274c |
completed | April 13, 2026, 7:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f79d5a23bc8190942568658665bbb0 |
completed | May 3, 2026, 7:09 p.m. |
Created at: April 9, 2026, 9:55 p.m.