Triple
T5112654
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Old French sire |
E115252
|
entity |
| Predicate | politenessType |
P20172
|
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: [Old French sire, politenessType, honorific]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: politenessType Context triple: [Old French sire, politenessType, honorific]
-
A.
politenessLevel
Indicates the degree of courteousness or respectfulness expressed by one entity toward another in an interaction.
-
B.
hasPolitePronoun
Indicates that one entity refers to another using a polite or honorific form of address in language.
-
C.
hasPolitenessSystem
Indicates that a language or communication system includes formalized ways of expressing different levels of politeness or social hierarchy.
-
D.
honorificType
chosen
Indicates the type or category of honorific or formal title associated with an entity in a given context.
-
E.
honorificUsage
Indicates that one entity refers to or addresses another using an honorific title or respectful linguistic form.
- 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_69bd4441d1648190a54a533895041987 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd75cba1e88190af076657f846b975 |
completed | March 20, 2026, 4:28 p.m. |
| PD | Predicate disambiguation | batch_69bd715fe3a8819087d3065adddba515 |
completed | March 20, 2026, 4:10 p.m. |
Created at: March 20, 2026, 1:41 p.m.