Triple
T32164865
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | M.J. Monahan |
E821536
|
entity |
| Predicate | worksInFictionalGenre |
P116833
|
FINISHED |
| Object | police thriller |
—
|
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: police thriller | Statement: [M.J. Monahan, worksInFictionalGenre, police thriller]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: worksInFictionalGenre Context triple: [M.J. Monahan, worksInFictionalGenre, police thriller]
-
A.
worksInFictionalContext
Indicates that an entity performs work or fulfills a role within a fictional or imagined setting rather than in real-world circumstances.
-
B.
worksWithInFiction
Indicates that two fictional characters are depicted as collaborating, interacting, or being associated with each other within a narrative work.
-
C.
createsInFiction
Indicates that one entity is the creator or originator of another entity within a fictional or narrative context.
-
D.
hasGenreInFiction
chosen
Indicates that a work of fiction belongs to or is categorized under a specific literary genre.
-
E.
livesInFiction
Indicates that one entity exists or resides within the fictional world or narrative setting created by another 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_69f3490699a48190bbef96b198e8fade |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f78c61ed4c8190ad84c918fa9af55a |
completed | May 3, 2026, 5:56 p.m. |
| PD | Predicate disambiguation | batch_69f78b8cb3a881909ebaac1b503988c2 |
completed | May 3, 2026, 5:53 p.m. |
Created at: May 1, 2026, 12:33 a.m.