Triple
T36203247
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mister President |
E1047322
|
entity |
| Predicate | formalOrInformal |
P4035
|
FINISHED |
| Object | formal |
—
|
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: formal | Statement: [Mister President, formalOrInformal, formal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: formalOrInformal Context triple: [Mister President, formalOrInformal, formal]
-
A.
isLessFormalThan
Indicates that one entity has a lower level of formality or is more casual in style, tone, or usage compared to another entity.
-
B.
formalityLevel
chosen
Indicates the degree of social or stylistic formality characterizing an interaction, expression, or context between entities.
-
C.
formalismFor
Indicates that one entity serves as a formal representation, framework, or notation specifically designed to model, describe, or reason about another entity.
-
D.
formalSetting
Indicates that the associated interaction, event, or context occurs in a formal or official setting governed by explicit social or institutional norms.
-
E.
hasInformalUsage
Indicates that something is used in casual or non-standard contexts rather than in formal or official usage.
- 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_69f76e414bdc8190996f15a544220a3d |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7be9d07ac8190adf796cbef60daf6 |
completed | May 3, 2026, 9:31 p.m. |
| PD | Predicate disambiguation | batch_69f7bcccd7988190aa5c931ff347d33c |
completed | May 3, 2026, 9:23 p.m. |
Created at: May 3, 2026, 4:08 p.m.