Triple
T20590564
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Disney live-action comedies |
E505909
|
entity |
| Predicate | ratingTrend |
P140683
|
FINISHED |
| Object | G |
—
|
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: G | Statement: [Disney live-action comedies, ratingTrend, G]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ratingTrend Context triple: [Disney live-action comedies, ratingTrend, G]
-
A.
rating
Indicates an evaluation relationship where one entity assigns a qualitative or quantitative score or judgment to another entity.
-
B.
ratingContext
Indicates the situational or contextual factors under which a rating is given or applies.
-
C.
ratingCategory
Indicates the qualitative classification or level assigned to a rating (e.g., low, medium, high) within an evaluation or scoring system.
-
D.
ratingOfWork
Indicates the evaluative score or assessment assigned to a particular work or creation.
-
E.
ratingDescription
Indicates the textual explanation or qualitative summary associated with a given rating or score.
- F. None of above. chosen
Provenance (4 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_69e0b4b9669c8190b8e81fc72817d42c |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6a97aaf1c81908006ae7447f1f503 |
completed | April 20, 2026, 10:32 p.m. |
| PD | Predicate disambiguation | batch_69e59fffe1748190825e4eaa90340631 |
completed | April 20, 2026, 3:39 a.m. |
| PDg | Predicate description generation | batch_69e5a6a9f3f88190b961db9aca36f7da |
completed | April 20, 2026, 4:08 a.m. |
Created at: April 16, 2026, 11:40 a.m.