Triple
T82997
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Madam President |
E1667
|
entity |
| Predicate | politeness |
P3329
|
FINISHED |
| Object | honorific |
—
|
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: honorific | Statement: [Madam President, politeness, honorific]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: politeness Context triple: [Madam President, politeness, honorific]
-
A.
politenessLevel
chosen
Indicates the degree of courteousness or respectfulness expressed by one entity toward another in an interaction.
-
B.
patronage
Indicates a relationship where one party supports, sponsors, or protects another, often in exchange for loyalty, services, or influence.
-
C.
plea
Indicates that a defendant formally states their response (such as guilty, not guilty, or no contest) to criminal charges in a legal proceeding.
-
D.
honors
Indicates that one entity shows respect, recognition, or esteem toward another entity, often in a formal or ceremonial way.
-
E.
stance
Indicates the position, attitude, or viewpoint one entity holds toward another entity, issue, or proposition.
- 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_69a24c8150408190910a693eb51c1f71 |
completed | Feb. 28, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69a25053ca208190a371b0d38000c2b9 |
completed | Feb. 28, 2026, 2:17 a.m. |
| PD | Predicate disambiguation | batch_69a24eb2998c819082681da74601d446 |
completed | Feb. 28, 2026, 2:10 a.m. |
Created at: Feb. 28, 2026, 2:06 a.m.