Triple
T1749032
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Obsessed |
E38396
|
entity |
| Predicate | ratingOnRottenTomatoes |
P8710
|
FINISHED |
| Object | generally negative critical reviews |
—
|
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 negative critical reviews | Statement: [Obsessed, ratingOnRottenTomatoes, generally negative critical reviews]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ratingOnRottenTomatoes Context triple: [Obsessed, ratingOnRottenTomatoes, generally negative critical reviews]
-
A.
rating
chosen
Indicates an evaluation relationship where one entity assigns a qualitative or quantitative score or judgment to another entity.
-
B.
ratingSystem
Indicates a system or method used to assign evaluative scores or rankings to items, actions, or entities based on defined criteria.
-
C.
USRating
Indicates that an entity has been assigned a rating, classification, or evaluation according to a United States–based standard or system.
-
D.
ratingExpectation
Indicates an anticipated or predicted evaluation score that one entity expects another entity to receive or assign.
-
E.
mpaaRating
Indicates the official Motion Picture Association of America (MPAA) content rating assigned to a film or audiovisual work.
- 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_69a8862bdb2081908aefe831c8aa8017 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69ab630e7d008190a8c673665d9672bb |
completed | March 6, 2026, 11:28 p.m. |
| PD | Predicate disambiguation | batch_69aa61c5a18481909bc49e0c54d64314 |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:31 p.m.