Triple
T12630158
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Majesty |
E301617
|
entity |
| Predicate | hasPolitenessType |
P94747
|
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: [Majesty, hasPolitenessType, honorific]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPolitenessType Context triple: [Majesty, hasPolitenessType, honorific]
-
A.
hasPolitenessSystem
Indicates that a language or communication system includes formalized ways of expressing different levels of politeness or social hierarchy.
-
B.
hasPolitePronoun
Indicates that one entity refers to another using a polite or honorific form of address in language.
-
C.
politenessLevel
Indicates the degree of courteousness or respectfulness expressed by one entity toward another in an interaction.
-
D.
hasManner
Indicates the way, style, or method in which an action is performed or a relation is carried out.
-
E.
hasHonorificType
chosen
Indicates that an entity is associated with a specific type or category of honorific title or form of address.
- 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_69d7bdeaf49c8190b13800111fa77ea3 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d961ae493481908f82e0d05dce20bd |
completed | April 10, 2026, 8:46 p.m. |
| PD | Predicate disambiguation | batch_69d960b47130819097e1162ed4fc993a |
completed | April 10, 2026, 8:42 p.m. |
Created at: April 9, 2026, 5:15 p.m.