Triple
T21971103
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Last Unicorn |
E542588
|
entity |
| Predicate | voiceActor |
P1507
|
FINISHED |
| Object | Tammy Grimes |
—
|
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: Tammy Grimes | Statement: [The Last Unicorn, voiceActor, Tammy Grimes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tammy Grimes Context triple: [The Last Unicorn, voiceActor, Tammy Grimes]
-
A.
Tammy Grimes
chosen
Tammy Grimes was an American actress and singer best known for her Tony Award–winning work on the Broadway stage, including originating the title role in "The Unsinkable Molly Brown."
-
B.
Tamara Greer
Tamara Greer is a person notable enough to be recognized as a significant bearer of the surname Greer.
-
C.
Tamara Tunie
Tamara Tunie is an American actress and director best known for her long-running role as medical examiner Melinda Warner on the television series "Law & Order: Special Victims Unit."
-
D.
Sherilyn Connelly
Sherilyn Connelly is a film producer best known for her work on the animated feature "The Tigger Movie."
-
E.
Kymberly Elise
Kymberly Elise is an American actress known for her powerful dramatic performances in film and television, including roles in works like "Beloved," "Set It Off," and "Diary of a Mad Black Woman."
- 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_69e0c48070988190909db97667b9a0ac |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f12484b83081908c08e3285e0b14a9 |
completed | April 28, 2026, 9:20 p.m. |
Created at: April 16, 2026, 8:02 p.m.