Triple
T20769324
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shantel VanSanten |
E511182
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Shantel |
—
|
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: Shantel | Statement: [Shantel VanSanten, givenName, Shantel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shantel Context triple: [Shantel VanSanten, givenName, Shantel]
-
A.
Shantel VanSanten
chosen
Shantel VanSanten is an American actress and model known for her roles in television series such as One Tree Hill, The Flash, and Shooter.
-
B.
Shanell
Shanell is an American singer-songwriter and dancer best known for her work with Lil Wayne’s Young Money Entertainment label.
-
C.
Dameisha
Dameisha is a popular coastal area in Shenzhen, China, best known for its long sandy beach, seaside resorts, and recreational attractions.
-
D.
Sherri
Sherri is an American daytime talk show hosted by comedian and actress Sherri Shepherd, known for its celebrity interviews, pop culture commentary, and comedic monologues.
-
E.
Schondra
Schondra is a small municipality in the Bavarian region of Lower Franconia in Germany.
- 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_69e0b4ca01148190ac018e57e0cab46f |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c24fa1b08190b09ab8fcb87b5c01 |
completed | April 21, 2026, 12:18 a.m. |
Created at: April 16, 2026, 12:36 p.m.