Triple
T20462340
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Man Against Crime |
E501955
|
entity |
| Predicate | hasTargetGenreCategory |
P140189
|
FINISHED |
| Object | mystery |
—
|
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: mystery | Statement: [Man Against Crime, hasTargetGenreCategory, mystery]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTargetGenreCategory Context triple: [Man Against Crime, hasTargetGenreCategory, mystery]
-
A.
hasTargetArtistGenre
Indicates that an entity (such as a campaign, recommendation, or product) is aimed at or associated with a specific music artist genre as its intended target.
-
B.
hasGenreEligibility
Indicates that an entity qualifies to be categorized under a particular genre according to defined criteria.
-
C.
hasUseGenre
Indicates that something (such as a work, product, or item) is associated with or categorized under a particular genre for its use or purpose.
-
D.
hasGenreAsSetting
Indicates that a work’s setting is characterized by, or takes place within, a particular genre.
-
E.
hasStageGenre
Indicates a relationship where a stage production or performance is associated with a particular theatrical or performance genre.
- 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_69e0b4ad4940819098cf2ff6413574e5 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e696a761648190b24cf4bb90a8abb1 |
completed | April 20, 2026, 9:12 p.m. |
| PD | Predicate disambiguation | batch_69e57679eb40819086142df3e39c928e |
completed | April 20, 2026, 12:42 a.m. |
| PDg | Predicate description generation | batch_69e58d766b408190a1d3698145fb6d30 |
completed | April 20, 2026, 2:20 a.m. |
Created at: April 16, 2026, 11:33 a.m.