Triple
T19993909
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dave Kelly |
E494133
|
entity |
| Predicate | collaboratedWith |
P435
|
FINISHED |
| Object | Tanya Stephens |
—
|
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: Tanya Stephens | Statement: [Dave Kelly, collaboratedWith, Tanya Stephens]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tanya Stephens Context triple: [Dave Kelly, collaboratedWith, Tanya Stephens]
-
A.
Tanya Stephens
chosen
Tanya Stephens is a Jamaican reggae and dancehall singer-songwriter known for her socially conscious lyrics and influential presence in Caribbean music.
-
B.
Tanya Wright
Tanya Wright is an American actress best known for her role as Crystal Burset on the television series "Orange Is the New Black."
-
C.
Stephanie Squires
Stephanie Squires is a central character in the coming-of-age film "The Wackness," serving as the love interest who helps drive the protagonist’s emotional and personal growth during a transformative summer in 1990s New York City.
-
D.
Tanya Reynolds
Tanya Reynolds is a British actress best known for her role as Lily Iglehart in the Netflix series "Sex Education."
-
E.
Stephanie Robinson
Stephanie Robinson is a personal name that may refer to multiple individuals across different fields, such as law, media, or academia.
- 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_69da626b2d748190886981ea90c8b2ea |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e65fe2036c8190b9f313215ad44e87 |
completed | April 20, 2026, 5:18 p.m. |
Created at: April 11, 2026, 3:31 p.m.