Triple
T30096556
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A Dictionary of Modern Slang, Cant, and Vulgar Words |
E764880
|
entity |
| Predicate | lexicalScope |
P61710
|
FINISHED |
| Object | non-standard English |
—
|
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: non-standard English | Statement: [A Dictionary of Modern Slang, Cant, and Vulgar Words, lexicalScope, non-standard English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lexicalScope Context triple: [A Dictionary of Modern Slang, Cant, and Vulgar Words, lexicalScope, non-standard English]
-
A.
scopeOfDeclaration
Indicates the syntactic region or context within which a particular declaration is valid and can be referenced.
-
B.
scopeOfReference
chosen
Indicates the range or domain of things, concepts, or entities to which a reference, statement, or expression applies.
-
C.
laterScope
Indicates that one event, state, or condition occurs or applies after the temporal scope of another.
-
D.
locationScope
Indicates the specific geographic or spatial area within which a given relationship, condition, or action is considered valid or applicable.
-
E.
encodingScope
Indicates the range or extent of content or information that is covered, represented, or captured by a particular encoding.
- 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_69f22474e4288190b5f895fe3974aa92 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f67d90de4881909fa48ca060068046 |
completed | May 2, 2026, 10:41 p.m. |
| PD | Predicate disambiguation | batch_69f673c664f08190b4d66cdc305e10db |
completed | May 2, 2026, 9:59 p.m. |
Created at: April 29, 2026, 7:07 p.m.