Triple
T2938646
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vicky Cristina Barcelona |
E79329
|
entity |
| Predicate | rottenTomatoesRating |
P37622
|
FINISHED |
| Object | generally positive |
—
|
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: generally positive | Statement: [Vicky Cristina Barcelona, rottenTomatoesRating, generally positive]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rottenTomatoesRating Context triple: [Vicky Cristina Barcelona, rottenTomatoesRating, generally positive]
-
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.
rating
Indicates an evaluation relationship where one entity assigns a qualitative or quantitative score or judgment to another entity.
-
E.
hasMetascore
Indicates that an entity is associated with a Metascore rating, typically representing an aggregated critical review score.
- 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_69ad8b0fbab081908f6a61567c045d8d |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad986c1c0c8190a6a9f17082438cfd |
completed | March 8, 2026, 3:40 p.m. |
| PD | Predicate disambiguation | batch_69ad96088fb481909976b436c2b729d9 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 2:56 p.m.