Triple
T4035253
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ex Machina |
E83811
|
entity |
| Predicate | hasRottenTomatoesApprovalRating |
P37622
|
FINISHED |
| Object | 92 |
—
|
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: 92 | Statement: [Ex Machina, hasRottenTomatoesApprovalRating, 92]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRottenTomatoesApprovalRating Context triple: [Ex Machina, hasRottenTomatoesApprovalRating, 92]
-
A.
hasRottenTomatoesRating
chosen
Indicates that an entity has an associated rating value assigned by Rotten Tomatoes.
-
B.
rottenTomatoesStatus
Indicates the critical or audience evaluation status of a work as represented on Rotten Tomatoes (e.g., fresh, rotten, or certified).
-
C.
hasRottenTomatoesEntry
Indicates that there exists a Rotten Tomatoes database entry corresponding to the given entity.
-
D.
hasMetascore
Indicates that an entity is associated with a Metascore rating, typically representing an aggregated critical review score.
-
E.
USRating
Indicates that an entity has been assigned a rating, classification, or evaluation according to a United States–based standard or 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_69aed92f7cf0819098e0539bdcc3767f |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefb132f6c8190937acd35a6a5a9e4 |
completed | March 9, 2026, 4:53 p.m. |
| PD | Predicate disambiguation | batch_69aef8fe440c819093a7fa22c4ff3f1a |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:36 p.m.