Triple
T19532660
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tameka "Tiny" Cottle |
E488692
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | Tameka Harris |
—
|
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 Harris | Statement: [Tameka "Tiny" Cottle, alsoKnownAs, Tameka Harris]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tameka Harris Context triple: [Tameka "Tiny" Cottle, alsoKnownAs, Tameka Harris]
-
A.
Tyasha Harris
Tyasha Harris is an American professional basketball player and standout point guard who starred for the University of South Carolina Gamecocks women’s basketball program.
-
B.
Tamika Scott
Tamika Scott is an American R&B singer and songwriter best known as a member of the multi-platinum 1990s girl group Xscape.
-
C.
Maya Harris
Maya Harris is an American lawyer, public policy advocate, and political strategist who has served as a senior advisor on major Democratic campaigns and in civil rights organizations.
-
D.
Tyisha Bogues
Tyisha Bogues is the daughter of former NBA point guard Muggsy Bogues.
-
E.
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.
- 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.