Triple
T14172438
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jaws of the Viper |
E351241
|
entity |
| Predicate | composerProfession |
P35550
|
FINISHED |
| Object | film and television composer |
—
|
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: film and television composer | Statement: [Jaws of the Viper, composerProfession, film and television composer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: composerProfession Context triple: [Jaws of the Viper, composerProfession, film and television composer]
-
A.
memberProfession
chosen
Indicates that a member or individual holds or practices a particular profession or occupation.
-
B.
professionalCategory
Indicates the classification of an entity according to its professional field, role, or occupational domain.
-
C.
professionalName
Indicates the formal name or title an entity uses in a professional or occupational context.
-
D.
developerOfWork
Indicates that one entity is the creator or producer responsible for making or developing a particular work.
-
E.
employedComposer
Indicates that one entity (such as a person or organization) employs another entity in the role of a composer.
- 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_69d8278834a08190b0f1784e58d7b99c |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61b5dcbc8190b0cfcce5e6c6d582 |
completed | April 14, 2026, 3:48 p.m. |
| PD | Predicate disambiguation | batch_69de05baed64819096590e5618a3a8ed |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 10, 2026, 1:01 a.m.