Triple
T33344509
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Republic of Zubrowka |
E853758
|
entity |
| Predicate | featuredGenreContext |
P203556
|
FINISHED |
| Object | comedy-drama |
—
|
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: comedy-drama | Statement: [Republic of Zubrowka, featuredGenreContext, comedy-drama]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuredGenreContext Context triple: [Republic of Zubrowka, featuredGenreContext, comedy-drama]
-
A.
playGenreContext
Indicates that an entity engages with or experiences a particular genre (e.g., of media or activity) within a specific contextual setting or situation.
-
B.
designGenre
Indicates that something belongs to, is characterized by, or is created in a particular design style or genre.
-
C.
targetGenre
Indicates the genre that something is specifically aimed at, categorized under, or intended to belong to.
-
D.
commonGenreContext
Indicates that two or more entities share a similar or related genre context, such as belonging to the same or closely related genres.
-
E.
genreIncludes
Indicates that a broader genre category encompasses or contains a specified subgenre or work as part of its classification.
- 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_69f3496a1a588190bad9cbe9221144e0 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a01a23d8b148190ac2c8765aa9227c4 |
completed | May 11, 2026, 9:32 a.m. |
| PD | Predicate disambiguation | batch_6a01a1e8bb90819096647e929bfb3db8 |
completed | May 11, 2026, 9:31 a.m. |
| PDg | Predicate description generation | batch_6a01a23ce3b08190acb03793824baf68 |
completed | May 11, 2026, 9:32 a.m. |
Created at: May 1, 2026, 1:34 a.m.