Triple
T30988416
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Linda Christian as Valerie Mathis |
E789595
|
entity |
| Predicate | adaptationOfCharacterType |
P60013
|
FINISHED |
| Object | Vesper Lynd analogue |
—
|
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: Vesper Lynd analogue | Statement: [Linda Christian as Valerie Mathis, adaptationOfCharacterType, Vesper Lynd analogue]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: adaptationOfCharacterType Context triple: [Linda Christian as Valerie Mathis, adaptationOfCharacterType, Vesper Lynd analogue]
-
A.
adaptationOfCharacterFrom
Indicates that one character is derived, modified, or reinterpreted from an existing character in another work or version.
-
B.
adaptationType
Indicates the specific kind or category of adaptation that relates one entity to another or to a particular context.
-
C.
typeOfCharacter
chosen
Indicates that one entity is a specific kind or category of character in relation to another entity.
-
D.
adaptationStar
Indicates that one work is an adaptation of another, with the subject being the adapted work and the object being the original source.
-
E.
adaptationAppearance
Indicates that one entity appears or is depicted in an adaptation of another entity (such as a work being represented in a derived or reinterpreted version).
- 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_69f224c550b081909ddfceb0c3d03bdd |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6c1bb5f248190834161b5a6ba1ece |
completed | May 3, 2026, 3:32 a.m. |
| PD | Predicate disambiguation | batch_69f6bd25bed08190befcabd3a41ffadf |
completed | May 3, 2026, 3:12 a.m. |
Created at: April 29, 2026, 8:56 p.m.