Triple
T985231
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Love, Antosha |
E21262
|
entity |
| Predicate | reviewAggregatorRating |
P8710
|
FINISHED |
| Object | Rotten Tomatoes positive critical reception |
—
|
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: Rotten Tomatoes positive critical reception | Statement: [Love, Antosha, reviewAggregatorRating, Rotten Tomatoes positive critical reception]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reviewAggregatorRating Context triple: [Love, Antosha, reviewAggregatorRating, Rotten Tomatoes positive critical reception]
-
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.
reviewsDecisionsFrom
Indicates that one entity examines and evaluates the decisions made by another entity.
-
D.
evaluationBasis
Indicates the criteria, standards, or reference framework used to judge, assess, or measure something in an evaluation process.
-
E.
reviewedBy
Indicates that an item, work, or action has been examined and evaluated by a specific agent or reviewer.
- 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_69a493c383dc8190a03257f22d4b4183 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b4959fe48190a78bd811cbc888ab |
completed | March 1, 2026, 9:50 p.m. |
| PD | Predicate disambiguation | batch_69a4b2abccbc8190a83af432f89eacf5 |
completed | March 1, 2026, 9:42 p.m. |
Created at: March 1, 2026, 7:41 p.m.