Triple
T26718933
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stana Katic as Kate Beckett |
E673645
|
entity |
| Predicate | portrayalLanguageAccent |
P61298
|
FINISHED |
| Object | American English |
—
|
LITERAL 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: American English | Statement: [Stana Katic as Kate Beckett, portrayalLanguageAccent, American English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portrayalLanguageAccent Context triple: [Stana Katic as Kate Beckett, portrayalLanguageAccent, American English]
-
A.
portrayalLanguage
Indicates the language in which something is depicted, represented, or expressed.
-
B.
voiceActorAccent
chosen
Indicates that a voice actor performs their role using a specified accent.
-
C.
voiceActingLanguage
Indicates the language in which a voice acting performance is delivered.
-
D.
speaksWithAccentWhenUsing
Indicates that an entity consistently uses a particular accent when using a specified language, medium, or communication mode.
-
E.
pronunciationLanguage
Indicates the language in which the pronunciation of an entity (such as a word or name) is given.
- F. None of above.
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_69eecda481d08190aea69f2f7c745f56 |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69f74062b9388190b30546cf700a825c |
completed | May 3, 2026, 12:32 p.m. |
| PD | Predicate disambiguation | batch_69f73c802b848190b61a416b7488bd96 |
completed | May 3, 2026, 12:16 p.m. |
Created at: April 27, 2026, 3:39 a.m.