Triple
T25713108
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Murder by Death |
E644785
|
entity |
| Predicate | parodiesCharacterType |
P10352
|
FINISHED |
| Object | Miss Marple-style detective |
—
|
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: Miss Marple-style detective | Statement: [Murder by Death, parodiesCharacterType, Miss Marple-style detective]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: parodiesCharacterType Context triple: [Murder by Death, parodiesCharacterType, Miss Marple-style detective]
-
A.
portrayedByCharacterType
Indicates that an entity is depicted or represented by a character of a specified type (e.g., hero, villain, sidekick) in a narrative or media work.
-
B.
depictsCharacterType
Indicates that one entity visually represents or portrays a character of a specified type or role.
-
C.
parodies
chosen
Indicates that one entity imitates another in an exaggerated or humorous way, often to criticize or comment on the original.
-
D.
isHumorousCharacter
Indicates that the character is portrayed in a humorous way or primarily serves a comedic role in the context.
-
E.
cultCharacter
Indicates that one entity is a character who is venerated, worshipped, or centrally revered within the cult associated with the other 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_69e77e83c8ec8190bf52fcdac4838984 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f5fc6008a4819084116248372fdd78 |
completed | May 2, 2026, 1:30 p.m. |
| PD | Predicate disambiguation | batch_69f4a0f7c6008190ae8cee3e71e19b94 |
completed | May 1, 2026, 12:47 p.m. |
Created at: April 21, 2026, 9:21 p.m.