Triple
T8722688
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ventura |
E207049
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Kelsey Gonzalez |
E320904
|
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: Kelsey Gonzalez | Statement: [Ventura, producer, Kelsey Gonzalez]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kelsey Gonzalez Context triple: [Ventura, producer, Kelsey Gonzalez]
-
A.
Kelsey Gonzalez
chosen
Kelsey Gonzalez is a visual artist and designer known for creating cover art, including work for the band Bush.
-
B.
Kelsey Burrell
Kelsey Burrell is known as the child of the Jamaican-American reggae fusion singer and rapper Shaggy.
-
C.
Brittany Gonzales
Brittany Gonzales is an American TV host and model best known as the wife of actor Kellan Lutz.
-
D.
Kelsey Asbille
Kelsey Asbille is an American actress known for her roles in television series such as Yellowstone and Teen Wolf, as well as films like Wind River.
-
E.
Kyla Ross
Kyla Ross is an American artistic gymnast, Olympic gold medalist, and multiple-time NCAA champion who became one of the most decorated athletes in collegiate gymnastics history.
- 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_69ca835811d8819081ea00fd2a2c9a1c |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5d0609f48190adc56226724b16c6 |
completed | March 31, 2026, 11:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf88cf76888190a0cdab7f30c791c7 |
completed | April 3, 2026, 9:30 a.m. |
Created at: March 30, 2026, 6:36 p.m.