Triple
T23303177
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lvovna |
E590360
|
entity |
| Predicate | usageFormality |
P4035
|
FINISHED |
| Object | formal address |
—
|
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 address | Statement: [Lvovna, usageFormality, formal address]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usageFormality Context triple: [Lvovna, usageFormality, formal address]
-
A.
formalityLevel
chosen
Indicates the degree of social or stylistic formality characterizing an interaction, expression, or context between entities.
-
B.
isLessFormalThan
Indicates that one entity has a lower level of formality or is more casual in style, tone, or usage compared to another entity.
-
C.
formalizationUses
Indicates that one formalization or formal system makes use of, depends on, or incorporates another resource, method, or framework in its construction or application.
-
D.
formalismFor
Indicates that one entity serves as a formal representation, framework, or notation specifically designed to model, describe, or reason about another entity.
-
E.
titleFormality
Indicates the degree of formality conveyed by a title used to address or refer to an entity.
- 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_69e25d1c0ecc8190a355aa229f06d0e0 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f19724de488190ac8eb89253c8dd53 |
completed | April 29, 2026, 5:29 a.m. |
| PD | Predicate disambiguation | batch_69effcf325f88190b320268c3c551abb |
completed | April 28, 2026, 12:18 a.m. |
Created at: April 17, 2026, 5:04 p.m.