Triple
T19386782
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Women Talking |
E484955
|
entity |
| Predicate | rotorTomatoesRatingApprox |
P37622
|
FINISHED |
| Object | above 85 percent |
—
|
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: above 85 percent | Statement: [Women Talking, rotorTomatoesRatingApprox, above 85 percent]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rotorTomatoesRatingApprox Context triple: [Women Talking, rotorTomatoesRatingApprox, above 85 percent]
-
A.
hasRottenTomatoesRating
chosen
Indicates that an entity has an associated rating value assigned by Rotten Tomatoes.
-
B.
hasRottenTomatoesEntry
Indicates that there exists a Rotten Tomatoes database entry corresponding to the given entity.
-
C.
rottenTomatoesStatus
Indicates the critical or audience evaluation status of a work as represented on Rotten Tomatoes (e.g., fresh, rotten, or certified).
-
D.
ratingOfWork
Indicates the evaluative score or assessment assigned to a particular work or creation.
-
E.
hasFilmScore
Indicates that one entity serves as the musical score or soundtrack composed for a particular film.
- 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_69d8e8d460d88190abf0591c5c9d2b0c |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e61b40d1148190b4fcd9ad56aa6910 |
completed | April 20, 2026, 12:25 p.m. |
| PD | Predicate disambiguation | batch_69e4fd602f008190aa9bc76ae17e4ce1 |
completed | April 19, 2026, 4:05 p.m. |
Created at: April 10, 2026, 1:36 p.m.