Triple
T10049119
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mark Wills |
E207695
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | I Do (Cherish You) |
E536213
|
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: I Do (Cherish You) | Statement: [Mark Wills, notableWork, I Do (Cherish You)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: I Do (Cherish You) Context triple: [Mark Wills, notableWork, I Do (Cherish You)]
-
A.
I Do (Cherish You)
chosen
"I Do (Cherish You)" is a romantic pop ballad best known from the late 1990s boy band 98 Degrees, often associated with weddings and love-themed playlists.
-
B.
I Do
"I Do" is a song featured on the album "Driving Rain" by Paul McCartney.
-
C.
I Do
"I Do" is a music album by Canadian actress and singer Jill Hennessy, showcasing her blend of folk, rock, and country influences.
-
D.
Like I Do
"Like I Do" is a song from Christina Aguilera’s album "Liberation," showcasing her blend of soulful vocals with contemporary pop and R&B production.
-
E.
Yes I Do
"Yes I Do" is a song performed by British actress and singer Carmen Ejogo, known for her work in film, television, and music.
- 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_69ca835ad0608190b7c80b292da004f5 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cdcf8cf4f0819084d831e1986790be |
completed | April 2, 2026, 2:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2829674f08190b5f9c3b984106469 |
completed | April 5, 2026, 3:41 p.m. |
Created at: March 30, 2026, 8:56 p.m.