Triple
T9879069
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bootylicious |
E240154
|
entity |
| Predicate | musicVideoDirector |
P4911
|
FINISHED |
| Object | Matthew Rolston |
E818854
|
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: Matthew Rolston | Statement: [Bootylicious, musicVideoDirector, Matthew Rolston]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Matthew Rolston Context triple: [Bootylicious, musicVideoDirector, Matthew Rolston]
-
A.
Matthew Rolston
chosen
Matthew Rolston is an American photographer and director renowned for his stylized celebrity portraiture and visually distinctive music videos.
-
B.
Matthew Rolph
Matthew Rolph is an American actor and comedian best known for his marriage to actress and comedian Mary Lynn Rajskub.
-
C.
Steve Ralston
Steve Ralston is a former American soccer midfielder best known as a longtime MLS standout and U.S. national team player, particularly with the New England Revolution.
-
D.
Matt Wolpert
Matt Wolpert is a television writer and producer best known for co-creating the alternate-history space drama series "For All Mankind."
-
E.
Matthew Shafer
Matthew Shafer is an American writer known for his work on the animated series "Cowboy Bebop" and related projects.
- 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_69ca84e8a0788190b9061811d50fd554 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb4135c108190b3330e929509699d |
completed | April 2, 2026, 12:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d87e177fcc81908613409c03995ea8 |
completed | April 10, 2026, 4:35 a.m. |
Created at: March 30, 2026, 8:37 p.m.