Triple
T14040599
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kiya Tomlin |
E337834
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Kiya Tomlin (clothing line) |
E337834
|
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: Kiya Tomlin (clothing line) | Statement: [Kiya Tomlin, notableWork, Kiya Tomlin (clothing line)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kiya Tomlin (clothing line) Context triple: [Kiya Tomlin, notableWork, Kiya Tomlin (clothing line)]
-
A.
Kiya Tomlin
chosen
Kiya Tomlin is an American fashion designer and entrepreneur known for her eponymous clothing line and custom womenswear.
-
B.
Karenna
Karenna is an American lawyer, author, and environmental activist best known as the daughter of former U.S. Vice President Al Gore.
-
C.
Annie Tee
Annie Tee is a central character in the television drama series "Treme," which explores life and culture in post-Katrina New Orleans.
-
D.
Tiffani
Tiffani is a given name, typically a modern variant of the name Tiffany used for girls.
-
E.
Tami-Lynn
Tami-Lynn is a fictional character best known as the foul-mouthed love interest of the talking teddy bear Ted in the comedy film series "Ted."
- 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_69d81c664e48819088cbd8f433aeffe5 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de311814e48190adb637e1c97c0658 |
completed | April 14, 2026, 12:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fbc33dbc8c819080b6cb3d589da7a1 |
completed | May 6, 2026, 10:39 p.m. |
Created at: April 9, 2026, 10:20 p.m.