Triple
T20622757
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Black Flag |
E506741
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Gimme Gimme Gimme |
—
|
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: Gimme Gimme Gimme | Statement: [Black Flag, notableWork, Gimme Gimme Gimme]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gimme Gimme Gimme Context triple: [Black Flag, notableWork, Gimme Gimme Gimme]
-
A.
Gimme Gimme Gimme
chosen
Gimme Gimme Gimme is a British sitcom centered on the chaotic lives of two mismatched flatmates, known for its crude humor and for helping establish Kathy Burke as a major comedy star.
-
B.
Gimme Some
"Gimme Some" is a track featured on the album "The Heat."
-
C.
Gimme
"Gimme" is a song released as a single by the artist Gloria.
-
D.
Please Gimme
Please Gimme is a whimsical character from Carl Sandburg’s children’s book collection "Rootabaga Stories," known for its playful, imaginative presence in the surreal American fairy tales.
-
E.
Me First and the Gimme Gimmes
Me First and the Gimme Gimmes is a punk rock supergroup known for performing fast, humorous cover versions of popular songs from various genres.
- 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_69e0b4bc90988190ac360aaf645efc1d |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6abe3177c8190ad1b2ca8b1e0a560 |
completed | April 20, 2026, 10:42 p.m. |
Created at: April 16, 2026, 11:42 a.m.