Triple
T19532673
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tameka "Tiny" Cottle |
E488692
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Tameka |
—
|
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: Tameka | Statement: [Tameka "Tiny" Cottle, givenName, Tameka]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tameka Context triple: [Tameka "Tiny" Cottle, givenName, Tameka]
-
A.
Shameika
"Shameika" is a critically acclaimed song by American singer-songwriter Fiona Apple from her 2020 album "Fetch the Bolt Cutters," noted for its unconventional structure and autobiographical lyrics about childhood resilience.
-
B.
Dameisha
Dameisha is a popular coastal area in Shenzhen, China, best known for its long sandy beach, seaside resorts, and recreational attractions.
-
C.
Tameka Foster
chosen
Tameka Foster is an American fashion stylist and television personality best known for her high-profile marriage to R&B singer Usher.
-
D.
LaTisha
LaTisha is a fictional female protagonist, likely a young woman or girl, who serves as the central focus of the story.
-
E.
Tamika
Tamika is a feminine given name most notably associated with retired American WNBA star and Hall of Fame basketball player Tamika Catchings.
- 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_69d8e8db5b6c8190984b61f91981f575 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6364091f4819088b27d0ffdf6010d |
completed | April 20, 2026, 2:20 p.m. |
Created at: April 10, 2026, 1:41 p.m.