Triple
T12060858
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frankenweenie (1984 short film) |
E287163
|
entity |
| Predicate | liveActionRemakeOf |
P103002
|
FINISHED |
| Object | Frankenstein concept |
—
|
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: Frankenstein concept | Statement: [Frankenweenie (1984 short film), liveActionRemakeOf, Frankenstein concept]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: liveActionRemakeOf Context triple: [Frankenweenie (1984 short film), liveActionRemakeOf, Frankenstein concept]
-
A.
hasRemake
Indicates that one work is a new version or recreation of an earlier existing work.
-
B.
remakeOfFilmStarring
Indicates that one film is a remake of another film in which a specified actor or set of actors starred.
-
C.
remakeFeature
Indicates that one work is a new version or adaptation created by redoing or updating the features of an earlier work.
-
D.
remakeDirector
Indicates that the subject is the director of a remake of the object work (e.g., film, show, or other media).
-
E.
remakeReleaseYear
Indicates the year in which a remake of an original work was released.
- 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_69d6ab4846e081908ee7bbd66a6d3459 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9100b4ca8819084845ca4c13e34ce |
completed | April 10, 2026, 2:58 p.m. |
| PD | Predicate disambiguation | batch_69d902bda47c8190b94860b31df4a98c |
completed | April 10, 2026, 2:01 p.m. |
| PDg | Predicate description generation | batch_69d91006e14081909838412df082f794 |
completed | April 10, 2026, 2:58 p.m. |
Created at: April 8, 2026, 9:48 p.m.