Triple
T28321041
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pride and Prejudice and Zombies |
E717279
|
entity |
| Predicate | authorOfAdaptedNovel |
P94269
|
FINISHED |
| Object | Seth Grahame-Smith |
—
|
NE NERFINISHED |
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: Seth Grahame-Smith | Statement: [Pride and Prejudice and Zombies, authorOfAdaptedNovel, Seth Grahame-Smith]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: authorOfAdaptedNovel Context triple: [Pride and Prejudice and Zombies, authorOfAdaptedNovel, Seth Grahame-Smith]
-
A.
adaptedAuthor
Indicates that one entity is the author whose work has been adapted by another entity (e.g., into a different medium or format).
-
B.
authorOfBookAdaptation
chosen
Indicates that one entity is the author of a book that has been adapted into another work (such as a film, series, or play).
-
C.
novelAdaptationCoAuthor
Indicates that the specified person is a co-author of a novel that is an adaptation of another work.
-
D.
adaptedWorkOfAuthor
Indicates that a work is an adaptation derived from, based on, or reinterpreting the original work of a specified author.
-
E.
authorOfInspiredWork
Indicates that one entity is the creator or originator of a work that has inspired another work or entity.
- 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_69eff6e6c3b08190ad78de6ba7f04548 |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69f7431c0eec81909ead443e07d75e18 |
completed | May 3, 2026, 12:44 p.m. |
| PD | Predicate disambiguation | batch_69f74143cf708190a12d487884298437 |
completed | May 3, 2026, 12:36 p.m. |
Created at: April 28, 2026, 12:24 a.m.