Triple
T14670749
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nana |
E344504
|
entity |
| Predicate | characterInWorkDescribedAs |
P115276
|
FINISHED |
| Object | darkly comic exploration of justice and revenge |
—
|
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: darkly comic exploration of justice and revenge | Statement: [Nana, characterInWorkDescribedAs, darkly comic exploration of justice and revenge]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterInWorkDescribedAs Context triple: [Nana, characterInWorkDescribedAs, darkly comic exploration of justice and revenge]
-
A.
characterIn
Indicates that an entity appears as a character within a specified work, story, or narrative.
-
B.
notableWorkCharacter
Indicates that a character appears in, is associated with, or plays a role in a particular notable work.
-
C.
character1
Indicates that the subject is identified as the first or primary character in a narrative or context.
-
D.
characterInBookBy
Indicates that a character appears in a book that was written by a specified author.
-
E.
characterDefinedBy
Indicates that one entity’s character, identity, or nature is determined, shaped, or specified by another entity.
- 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_69d822e283fc8190a0e4c235cf880052 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb54ef2908190b189ced65eec434a |
completed | April 14, 2026, 9:44 p.m. |
| PD | Predicate disambiguation | batch_69de6576f0208190aa94d995e797ac38 |
completed | April 14, 2026, 4:04 p.m. |
| PDg | Predicate description generation | batch_69de716c17cc8190aeb85296abee85a7 |
completed | April 14, 2026, 4:55 p.m. |
Created at: April 10, 2026, 1:27 a.m.