Triple
T32280415
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Madam President |
E824672
|
entity |
| Predicate | politenessForm |
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: [Madam President, politenessForm, formal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: politenessForm Context triple: [Madam President, politenessForm, formal]
-
A.
politenessLevel
Indicates the degree of courteousness or respectfulness expressed by one entity toward another in an interaction.
-
B.
politenessStrategy
Indicates the type of communicative approach or tactic used to express politeness in an interaction between entities.
-
C.
hasPolitePronoun
Indicates that one entity refers to another using a polite or honorific form of address in language.
-
D.
hasPolitenessSystem
Indicates that a language or communication system includes formalized ways of expressing different levels of politeness or social hierarchy.
-
E.
formalityLevel
chosen
Indicates the degree of social or stylistic formality characterizing an interaction, expression, or context between entities.
- 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_69f3490f404081908450db66884f4334 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fdd2be648c8190b60b3d1caeb44364 |
completed | May 8, 2026, 12:10 p.m. |
| PD | Predicate disambiguation | batch_69fdd14a5c708190a6f95ec61f4fc28f |
completed | May 8, 2026, 12:04 p.m. |
Created at: May 1, 2026, 12:43 a.m.