Triple
T18094003
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Keep Me in Your Heart |
E433037
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Don Was |
—
|
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: Don Was | Statement: [Keep Me in Your Heart, producer, Don Was]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Don Was Context triple: [Keep Me in Your Heart, producer, Don Was]
-
A.
Don Was
chosen
Don Was is an American musician and Grammy-winning record producer best known for his work with artists across rock, blues, and pop, and as the longtime president of Blue Note Records.
-
B.
Johnny Was
"Johnny Was" is a socially conscious reggae song by Bob Marley and the Wailers, known for its poignant storytelling about violence and loss.
-
C.
Don Most
Don Most is an American actor and singer best known for playing Ralph Malph on the classic television sitcom "Happy Days."
-
D.
Don Paul
Don Paul is an American film director and animator best known for co-directing the DreamWorks animated feature "The Road to El Dorado."
-
E.
Hal Walker
Hal Walker was an American film director best known for his work on mid-20th-century Hollywood comedies, including several popular Bing Crosby and Bob Hope "Road to..." films.
- 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_69d8b907d05c819083cc3bd6021089e6 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4dd1a75048190924ebc01da83851b |
completed | April 19, 2026, 1:48 p.m. |
Created at: April 10, 2026, 10:27 a.m.