Triple
T6456981
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tina Weymouth |
E142016
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Tina Weymouth |
E142016
|
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: Tina Weymouth | Statement: [Tina Weymouth, name, Tina Weymouth]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tina Weymouth Context triple: [Tina Weymouth, name, Tina Weymouth]
-
A.
Tina Weymouth
chosen
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.
-
B.
Maureen Tucker
Maureen Tucker is an American musician best known as the pioneering, minimalist drummer of the influential rock band The Velvet Underground.
-
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 (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_69c008d2f91c8190a8178767a35e08fc |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c069d639ec8190bb0a806da4118440 |
completed | March 22, 2026, 10:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c64bdc4e808190a7c24b963ab0aa30 |
completed | March 27, 2026, 9:20 a.m. |
Created at: March 22, 2026, 4:48 p.m.