Triple
T38671450
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | George Schenck |
E940604
|
entity |
| Predicate | hasWritingCreditInGenre |
P14417
|
FINISHED |
| Object | crime drama television series |
—
|
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: crime drama television series | Statement: [George Schenck, hasWritingCreditInGenre, crime drama television series]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWritingCreditInGenre Context triple: [George Schenck, hasWritingCreditInGenre, crime drama television series]
-
A.
hasWritingCreditOn
Indicates that an entity is credited as a writer or co-writer for a particular work or production.
-
B.
hasWorkInGenreOfAuthor
Indicates that a work is associated with an author whose typical or primary genre matches the genre of that work.
-
C.
hasGivenGenreDefiningWork
Indicates that an entity has created or produced a work that is widely regarded as defining or fundamentally shaping a particular genre.
-
D.
workedOnGenre
chosen
Indicates that an entity (such as a person or organization) has done work related to a particular genre.
-
E.
hasGenreOfWorkItAppearsIn
Indicates that an entity is associated with the genre of the work in which it appears.
- 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_69f76edfde348190bf6529d9f49ecd62 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fcdfbc71c481908ba7f87907b17782 |
completed | May 7, 2026, 6:53 p.m. |
| PD | Predicate disambiguation | batch_69fcdbe580b8819087f143596b2c79c0 |
completed | May 7, 2026, 6:37 p.m. |
Created at: May 3, 2026, 4:33 p.m.