Triple
T18879242
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Caity Lotz |
E461777
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Caity Lotz |
—
|
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: Caity Lotz | Statement: [Caity Lotz, name, Caity Lotz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Caity Lotz Context triple: [Caity Lotz, name, Caity Lotz]
-
A.
Caity Lotz
chosen
Caity Lotz is an American actress, dancer, and director best known for her role as Sara Lance/White Canary in the Arrowverse television series, particularly DC's Legends of Tomorrow.
-
B.
Deborah Anne Mazar
Deborah Anne Mazar is an American actress known for her sharp-tongued, tough-girl roles in film and television, including notable appearances in "Goodfellas," "Entourage," and "Younger."
-
C.
Kaitlin Olson
Kaitlin Olson is an American actress and comedian best known for playing Dee Reynolds on the long-running sitcom "It's Always Sunny in Philadelphia."
-
D.
Kaya Faison
Kaya Faison is one of the children of the late nurse Lisa Askey and actor Donald Faison.
-
E.
Kiernan Shipka
Kiernan Shipka is an American actress best known for her leading roles in the series Mad Men and Chilling Adventures of Sabrina.
- 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_69d8dcfc3430819095ee6fc0eb4c06a5 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5c3d06ef481908bba297d7a1fd011 |
completed | April 20, 2026, 6:12 a.m. |
Created at: April 10, 2026, 11:57 a.m.