Triple
T6788734
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | America’s Court with Judge Ross |
E155877
|
entity |
| Predicate | belongsToGenreCategory |
P62560
|
FINISHED |
| Object | American legal television series |
—
|
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: American legal television series | Statement: [America’s Court with Judge Ross, belongsToGenreCategory, American legal television series]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: belongsToGenreCategory Context triple: [America’s Court with Judge Ross, belongsToGenreCategory, American legal television series]
-
A.
hasGenreInRoles
Indicates that an entity participates in roles associated with a particular genre or set of genres.
-
B.
belongsToWorkGenre
chosen
Indicates that a creative work is classified under or associated with a particular genre.
-
C.
hasGenreScope
Indicates that something (such as a work, collection, or classification) is limited to, defined by, or applicable within a particular genre or set of genres.
-
D.
containsGenreElement
Indicates that something includes or incorporates an element characteristic of a particular genre.
-
E.
hasGenreOfClaim
Indicates that a claim is categorized or classified under a particular genre or type of claim.
- 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_69c6881770fc8190972b2906390380f5 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d2aa2e0c8190b994261826ae001d |
completed | March 27, 2026, 6:55 p.m. |
| PD | Predicate disambiguation | batch_69c6d0979ce0819094678896da4e3169 |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:14 p.m.