Triple
T30239162
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | At the Movies (Australian TV program) |
E768858
|
entity |
| Predicate | reviewStyle |
P40782
|
FINISHED |
| Object | star ratings |
—
|
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: star ratings | Statement: [At the Movies (Australian TV program), reviewStyle, star ratings]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reviewStyle Context triple: [At the Movies (Australian TV program), reviewStyle, star ratings]
-
A.
reviewFormat
chosen
Indicates the specific structure, style, or medium in which a review is presented or delivered.
-
B.
reviewType
Indicates the specific category or kind of review associated with an item, action, or relationship.
-
C.
reviewMethod
Indicates the method or process by which something is examined, evaluated, or reviewed.
-
D.
reviewBody
Indicates the textual content of a review that expresses an evaluator’s opinions, comments, or feedback about something.
-
E.
reviewOf
Indicates that one entity is a critical or evaluative assessment that is about or directed toward 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_69f224820c048190b1435c4cc145acf1 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f6804d6ef081908267e0f6dc644557 |
completed | May 2, 2026, 10:53 p.m. |
| PD | Predicate disambiguation | batch_69f6760216108190bbb708d53a6c2c25 |
completed | May 2, 2026, 10:09 p.m. |
Created at: April 29, 2026, 7:38 p.m.