Triple
T17341721
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | To Love Somebody |
E421081
|
entity |
| Predicate | hasCoverVersionBy |
P11142
|
FINISHED |
| Object | Michael Bublé |
E114853
|
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: Michael Bublé | Statement: [To Love Somebody, hasCoverVersionBy, Michael Bublé]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michael Bublé Context triple: [To Love Somebody, hasCoverVersionBy, Michael Bublé]
-
A.
Michael Bublé
chosen
Michael Bublé is a Canadian singer and songwriter renowned for his smooth vocals and modern interpretations of traditional pop and jazz standards.
-
B.
Josh Groban
Josh Groban is an American singer, songwriter, and actor known for his powerful baritone voice and crossover classical-pop ballads.
-
C.
Eric Benét
Eric Benét is an American R&B and neo-soul singer, songwriter, and actor known for his smooth vocals and romantic ballads.
-
D.
Alan Willis Thicke
Alan Willis Thicke was a Canadian actor, songwriter, and television host best known for his role as Jason Seaver on the sitcom "Growing Pains."
-
E.
John Tedder
John Tedder is known primarily as the son of Arthur Tedder, the prominent British air marshal and senior Royal Air Force commander during World War II.
- 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_69d889d3adc881909319f1edb8d2a956 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43a173e1c8190afcebf25ee902cc8 |
completed | April 19, 2026, 2:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a018c588a7081909ab108cb4adfedfe |
completed | May 11, 2026, 7:59 a.m. |
Created at: April 10, 2026, 5:44 a.m.