Triple
T9298976
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Casino Royale (1954 TV production) |
E223711
|
entity |
| Predicate | characterCorrespondsTo |
P87918
|
FINISHED |
| Object | Valerie Mathis as adaptation of Vesper Lynd |
—
|
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: Valerie Mathis as adaptation of Vesper Lynd | Statement: [Casino Royale (1954 TV production), characterCorrespondsTo, Valerie Mathis as adaptation of Vesper Lynd]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterCorrespondsTo Context triple: [Casino Royale (1954 TV production), characterCorrespondsTo, Valerie Mathis as adaptation of Vesper Lynd]
-
A.
containsCharacter
Indicates that one entity includes a specific character as part of its content or composition.
-
B.
correspondsToChineseCharacter
Indicates that one entity is the equivalent or representation of a specific Chinese written character.
-
C.
characterForm
Indicates that one entity is a particular form, version, or transformation state of a character.
-
D.
character3
Indicates a tertiary or additional character role associated with an entity, typically the third distinct character linked within a given context or work.
-
E.
character2
Indicates that a second character entity is involved in the relationship or context defined by the predicate.
- F. None of above. chosen
Provenance (4 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_69ca8423edb08190bc0c91287a484768 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd08cf50cc8190a025f478dff4f9fd |
completed | April 1, 2026, noon |
| PD | Predicate disambiguation | batch_69cc7a5ef1908190bc5ca166bb895af6 |
completed | April 1, 2026, 1:52 a.m. |
| PDg | Predicate description generation | batch_69cc95597be081908ece2491dd2f0f74 |
completed | April 1, 2026, 3:47 a.m. |
Created at: March 30, 2026, 7:36 p.m.