Triple
T20621697
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sweet Jane |
E506712
|
entity |
| Predicate | drummer |
P15280
|
FINISHED |
| Object | Moe Tucker |
—
|
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: Moe Tucker | Statement: [Sweet Jane, drummer, Moe Tucker]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Moe Tucker Context triple: [Sweet Jane, drummer, Moe Tucker]
-
A.
Maureen Tucker
chosen
Maureen Tucker is an American musician best known as the pioneering, minimalist drummer of the influential rock band The Velvet Underground.
-
B.
Tina Weymouth
Tina Weymouth is an American bassist, singer, and songwriter best known as a founding member of the influential new wave band Talking Heads and the Tom Tom Club.
-
C.
Deborah Harry
Deborah Harry is an American singer, songwriter, and actress best known as the lead vocalist of the new wave band Blondie.
-
D.
Mary Perkins
Mary Perkins was the mother of American educator and naturalist Elizabeth Cabot Agassiz.
-
E.
Maureen Van Zandt
Maureen Van Zandt is an American actress and producer best known for her role as Gabriella Dante on the television series "The Sopranos."
- 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_69e6abe25c208190af057bcd1aa6219d |
completed | April 20, 2026, 10:42 p.m. |
Created at: April 16, 2026, 11:42 a.m.