Triple
T2173476
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | G |
E48474
|
entity |
| Predicate | ratingMeaning |
P37395
|
FINISHED |
| Object | general audiences |
—
|
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: general audiences | Statement: [G, ratingMeaning, general audiences]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ratingMeaning Context triple: [G, ratingMeaning, general audiences]
-
A.
rating
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.
ratingExpectation
Indicates an anticipated or predicted evaluation score that one entity expects another entity to receive or assign.
-
D.
rankingPoints
Indicates the number of points assigned to an entity based on its position or performance in a ranking or competition.
-
E.
scoreScale
Indicates the scale or range on which a score or rating is expressed or measured.
- 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_69a88aa3faa48190995b233af6525815 |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc1559ff481908efe3f214b2570dc |
completed | March 7, 2026, 6:10 a.m. |
| PD | Predicate disambiguation | batch_69abbd9efc1c81909a65044a1ffc9038 |
completed | March 7, 2026, 5:54 a.m. |
| PDg | Predicate description generation | batch_69abc153b22481908115e5f582c93f12 |
completed | March 7, 2026, 6:10 a.m. |
Created at: March 4, 2026, 7:45 p.m.