Triple
T25747460
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bahamian Patwa |
E648380
|
entity |
| Predicate | hasTypicalRegister |
P44024
|
FINISHED |
| Object | informal |
—
|
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: informal | Statement: [Bahamian Patwa, hasTypicalRegister, informal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalRegister Context triple: [Bahamian Patwa, hasTypicalRegister, informal]
-
A.
hasStandardRegister
Indicates that something is expressed or occurs in a standard, neutral, or non-marked linguistic register.
-
B.
typicalRegister
chosen
Indicates the usual or most common linguistic register (e.g., formal, informal, technical) in which something—such as a word, expression, or communication—is typically used.
-
C.
hasRegister
Indicates that one entity possesses, contains, or is associated with a specific register (such as a record, log, or hardware register).
-
D.
hasRegistrationType
Indicates that an entity is associated with a specific category or type of registration it holds or requires.
-
E.
hasTypicalCharacterType
Indicates that an entity is commonly associated with or exemplified by a particular type of character or persona.
- 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_69e7ab306eec8190b05c312c6ab186b8 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f6b2a65c7c8190ac40f1466ceadefc |
completed | May 3, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69f6b14d7d508190bc7d4c89dfba4a32 |
completed | May 3, 2026, 2:22 a.m. |
Created at: April 22, 2026, 3:52 a.m.