Triple
T22579023
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bitter Sweet |
E544514
|
entity |
| Predicate | hasTrack |
P3284
|
FINISHED |
| Object | Work To Do |
—
|
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: Work To Do | Statement: [Bitter Sweet, hasTrack, Work To Do]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Work To Do Context triple: [Bitter Sweet, hasTrack, Work To Do]
-
A.
Work to Do
chosen
"Work to Do" is a funk and soul song popularized by the Scottish band Average White Band, known for its energetic groove and tight horn arrangements.
-
B.
Worky
Worky is the commonly used nickname for Workington Town Rugby League Football Club, a professional rugby league team based in Workington, Cumbria, England.
-
C.
To Do
To Do is Microsoft's cloud-based task management application that helps users organize and track personal and work-related tasks across devices.
-
D.
Do the Work
Do the Work is a motivational self-help book by Steven Pressfield that guides readers through overcoming resistance and procrastination to complete creative and entrepreneurial projects.
-
E.
Working
"Working" is a musical by Stephen Schwartz that adapts Studs Terkel’s book of interviews into a series of vignettes exploring the lives and aspirations of everyday American workers.
- 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_69e11e30d05481909df915354c89f0d6 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f15fefa1308190876b617d47ba08f3 |
completed | April 29, 2026, 1:33 a.m. |
Created at: April 16, 2026, 8:53 p.m.