Triple
T1449497
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rob |
E31255
|
entity |
| Predicate | typicalFormalityLevel |
P4035
|
FINISHED |
| Object | informal |
—
|
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: informal | Statement: [Rob, typicalFormalityLevel, informal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalFormalityLevel Context triple: [Rob, typicalFormalityLevel, informal]
-
A.
formalityLevel
chosen
Indicates the degree of social or stylistic formality characterizing an interaction, expression, or context between entities.
-
B.
typicalForm
Indicates that one entity represents the standard, characteristic, or most common form or shape in which another entity typically appears or is realized.
-
C.
politenessLevel
Indicates the degree of courteousness or respectfulness expressed by one entity toward another in an interaction.
-
D.
typicalGradeLevel
Indicates the usual or most common educational grade level at which something (such as a concept, resource, or skill) is intended to be taught or is typically encountered.
-
E.
typicalDegree
Indicates the usual or characteristic level, intensity, or extent to which something holds or applies in a given context.
- 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_69a499171a28819085b993a3ac78e363 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c55c408c8190917ed44d9070a2fb |
completed | March 1, 2026, 11:01 p.m. |
| PD | Predicate disambiguation | batch_69a4c47a840c819083307a65c027a19e |
completed | March 1, 2026, 10:58 p.m. |
Created at: March 1, 2026, 8 p.m.