Triple
T10198157
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Riley Andersen |
E238815
|
entity |
| Predicate | portrayedByVoice |
P13156
|
FINISHED |
| Object | Kaitlyn Dias |
E262249
|
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: Kaitlyn Dias | Statement: [Riley Andersen, portrayedByVoice, Kaitlyn Dias]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kaitlyn Dias Context triple: [Riley Andersen, portrayedByVoice, Kaitlyn Dias]
-
A.
Kaitlyn Dias
chosen
Kaitlyn Dias is an American actress best known for voicing the character Riley Andersen in Pixar's animated film "Inside Out."
-
B.
Kaitlyn Black
Kaitlyn Black is an American actress best known for her role as Annabeth Nass on the television series "Hart of Dixie."
-
C.
Kaitlyn Robrock
Kaitlyn Robrock is an American voice actress best known for portraying iconic animated characters, including serving as the current voice of Minnie Mouse for Disney.
-
D.
Kaitlyn Dunn
Kaitlyn Dunn is a person notable enough to be specifically referenced as a bearer of the surname Dunn.
-
E.
Kendall Gill
Kendall Gill is a former American professional basketball player best known for his NBA career as a high-scoring guard and strong defender in the 1990s.
- 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_69ca84e1ea088190b38162e43d4cfa8f |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdee3c44408190b09fa41f2d257c04 |
completed | April 2, 2026, 4:19 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d6f6e73a2881908563e9e6a02df944 |
completed | April 9, 2026, 12:46 a.m. |
Created at: March 30, 2026, 9:13 p.m.