Triple
T2124790
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Up |
E46400
|
entity |
| Predicate | RottenTomatoesRating |
P8710
|
FINISHED |
| Object | very high approval rating |
—
|
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: very high approval rating | Statement: [Up, RottenTomatoesRating, very high approval rating]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: RottenTomatoesRating Context triple: [Up, RottenTomatoesRating, very high approval rating]
-
A.
rating
chosen
Indicates an evaluation relationship where one entity assigns a qualitative or quantitative score or judgment to another entity.
-
B.
USRating
Indicates that an entity has been assigned a rating, classification, or evaluation according to a United States–based standard or system.
-
C.
mpaaRating
Indicates the official Motion Picture Association of America (MPAA) content rating assigned to a film or audiovisual work.
-
D.
ratingExpectation
Indicates an anticipated or predicted evaluation score that one entity expects another entity to receive or assign.
-
E.
ratingSystem
Indicates a system or method used to assign evaluative scores or rankings to items, actions, or entities based on defined criteria.
- 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_69a88a1626548190ae59a5028c3baa8e |
completed | March 4, 2026, 7:37 p.m. |
| NER | Named-entity recognition | batch_69abbb57bc6881909f04a407beff33a6 |
completed | March 7, 2026, 5:44 a.m. |
| PD | Predicate disambiguation | batch_69abb7bd86cc8190938ef06c1ed6d969 |
completed | March 7, 2026, 5:29 a.m. |
Created at: March 4, 2026, 7:44 p.m.