Triple
T7419773
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | One Minute Man |
E171214
|
entity |
| Predicate | featuredArtist |
P997
|
FINISHED |
| Object | Trina |
E124262
|
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: Trina | Statement: [One Minute Man, featuredArtist, Trina]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Trina Context triple: [One Minute Man, featuredArtist, Trina]
-
A.
Trina
chosen
Trina is an American rapper known for her sexually explicit lyrics, confident persona, and influential role in Southern hip hop, particularly Miami’s rap scene.
-
B.
Tricia
Tricia is a feminine given name commonly used as a shortened or informal form of Patricia.
-
C.
Tori
Tori is a common diminutive or nickname for the given name Victoria.
-
D.
Trisha
Trisha is a prominent Indian actress best known for her leading roles in Tamil films and her significant impact on South Indian cinema.
-
E.
Tina
Tina is the nickname of Tina Fey, an American comedian, writer, actress, and producer best known for her work on Saturday Night Live and 30 Rock.
- 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_69c68a625d048190af70eb8b63bec5a0 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f2ea61248190886e8e55b42ba5f1 |
completed | March 27, 2026, 9:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c81ef7fc808190a564ab4d9d97ab37 |
completed | March 28, 2026, 6:33 p.m. |
Created at: March 27, 2026, 3:11 p.m.