Triple
T20462926
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PG-13 |
E501971
|
entity |
| Predicate | hasParticularMeaning |
P3918
|
FINISHED |
| Object | play on MPAA film rating PG-13 |
—
|
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: play on MPAA film rating PG-13 | Statement: [PG-13, hasParticularMeaning, play on MPAA film rating PG-13]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasParticularMeaning Context triple: [PG-13, hasParticularMeaning, play on MPAA film rating PG-13]
-
A.
hasParticularSignificanceFor
Indicates that something holds a special, notable, or contextually important relevance or impact for a particular entity or situation.
-
B.
hasMeaningCategory
Indicates that something is associated with a particular category of meaning or semantic type.
-
C.
hasLiteralMeaning
chosen
Indicates that one entity expresses the direct, explicit meaning or sense of another entity (such as a word, phrase, or symbol).
-
D.
hasMeaningViaJohn
Indicates that something possesses or conveys its meaning specifically through John as the interpretive or mediating agent.
-
E.
hasMultipleMeanings
Indicates that a term, symbol, or expression is associated with more than one distinct meaning or interpretation.
- 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_69e0b4ad4940819098cf2ff6413574e5 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e696a761648190b24cf4bb90a8abb1 |
completed | April 20, 2026, 9:12 p.m. |
| PD | Predicate disambiguation | batch_69e57679eb40819086142df3e39c928e |
completed | April 20, 2026, 12:42 a.m. |
Created at: April 16, 2026, 11:33 a.m.