Triple
T10975015
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kenneth Branagh as Victor Frankenstein |
E259347
|
entity |
| Predicate | relationshipToCreature |
P96394
|
FINISHED |
| Object | creator |
—
|
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: creator | Statement: [Kenneth Branagh as Victor Frankenstein, relationshipToCreature, creator]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToCreature Context triple: [Kenneth Branagh as Victor Frankenstein, relationshipToCreature, creator]
-
A.
relationshipToHumans
Indicates the nature or type of connection, association, or relevance that something has specifically with humans.
-
B.
associationWithHumans
Indicates a general relationship, connection, or involvement between an entity and one or more humans.
-
C.
associatedBeings
Indicates that two or more beings are linked or connected to each other in some relevant way.
-
D.
usesCreature
Indicates that one entity employs, controls, or relies on a creature to perform an action or fulfill a function.
-
E.
relationshipToCharacter
Indicates the specific type of personal, social, or narrative connection that one entity has to a given character.
- 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_69d6aa895f4c8190887a15460ef622f4 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d771f4e888819097433271a2f45ff3 |
completed | April 9, 2026, 9:31 a.m. |
| PD | Predicate disambiguation | batch_69d72e8c27cc81908050590b7a04cafd |
completed | April 9, 2026, 4:43 a.m. |
| PDg | Predicate description generation | batch_69d732242fdc8190be77d1f730a42935 |
completed | April 9, 2026, 4:59 a.m. |
Created at: April 8, 2026, 9:24 p.m.