Triple
T4525910
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Honey Ryder |
E103375
|
entity |
| Predicate | portrayalAccentedAs |
P14722
|
FINISHED |
| Object | Swiss-accented English (original performance) |
—
|
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: Swiss-accented English (original performance) | Statement: [Honey Ryder, portrayalAccentedAs, Swiss-accented English (original performance)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portrayalAccentedAs Context triple: [Honey Ryder, portrayalAccentedAs, Swiss-accented English (original performance)]
-
A.
accentedFormOf
Indicates that one linguistic form is an accented or diacritically marked variant of another, more basic form.
-
B.
hasAccent
chosen
Indicates that an entity speaks with or possesses a particular accent or distinctive pronunciation style.
-
C.
portrayalFeature
Indicates that one entity serves as a characteristic, aspect, or attribute highlighted in the depiction or representation of another entity.
-
D.
portrayalRecognition
Indicates that one entity recognizes or identifies another entity as a portrayal or representation of a particular subject or character.
-
E.
portrayalLedTo
Indicates that one entity’s portrayal of another caused or significantly contributed to a subsequent outcome, reaction, or state involving that other entity.
- 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_69bd43dba59881908cf59b31df8c7ae1 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd577490f48190ac1fb3cbf3d8a41e |
completed | March 20, 2026, 2:19 p.m. |
| PD | Predicate disambiguation | batch_69bd521cf77c819083852de3094d1377 |
completed | March 20, 2026, 1:56 p.m. |
Created at: March 20, 2026, 1:03 p.m.