Triple
T29372110
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Splatterhouse |
E744880
|
entity |
| Predicate | ratingIssue |
P48179
|
FINISHED |
| Object | censorship in some regions |
—
|
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: censorship in some regions | Statement: [Splatterhouse, ratingIssue, censorship in some regions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ratingIssue Context triple: [Splatterhouse, ratingIssue, censorship in some regions]
-
A.
rating
Indicates an evaluation relationship where one entity assigns a qualitative or quantitative score or judgment to another entity.
-
B.
ratingContext
chosen
Indicates the situational or contextual factors under which a rating is given or applies.
-
C.
ratingContent
Indicates that an entity evaluates or assigns a quality or satisfaction score to some content.
-
D.
ratingDescription
Indicates the textual explanation or qualitative summary associated with a given rating or score.
-
E.
ratingCategory
Indicates the qualitative classification or level assigned to a rating (e.g., low, medium, high) within an evaluation or scoring system.
- 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_69f0a79ba954819094597628112c6091 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69f669ab36008190bc2e3c5dbdd2050d |
completed | May 2, 2026, 9:16 p.m. |
| PD | Predicate disambiguation | batch_69f6659b62fc8190b21555d0ba54db2d |
completed | May 2, 2026, 8:59 p.m. |
Created at: April 28, 2026, 2:28 p.m.