Triple
T3390036
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blue Dress B |
E71394
|
entity |
| Predicate | relativeFormality |
P4035
|
FINISHED |
| Object | less formal than Blue Dress A |
—
|
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: less formal than Blue Dress A | Statement: [Blue Dress B, relativeFormality, less formal than Blue Dress A]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relativeFormality Context triple: [Blue Dress B, relativeFormality, less formal than Blue Dress A]
-
A.
formalityLevel
chosen
Indicates the degree of social or stylistic formality characterizing an interaction, expression, or context between entities.
-
B.
politenessLevel
Indicates the degree of courteousness or respectfulness expressed by one entity toward another in an interaction.
-
C.
formalismType
Indicates the specific formal system or representational framework in which something (such as a theory, model, or specification) is expressed.
-
D.
relativeComfort
Indicates a comparative relationship where one entity is judged to be more or less comfortable than another under given conditions.
-
E.
formalizedUnder
Indicates that something has been officially established, defined, or codified within the framework, authority, or provisions of a particular formal system, agreement, or institution.
- 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_69ad85a9c4a88190a854019341cb3b60 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb666e514819090560d43bfaf55b8 |
completed | March 8, 2026, 5:48 p.m. |
| PD | Predicate disambiguation | batch_69adadf705608190975423779430cc58 |
completed | March 8, 2026, 5:12 p.m. |
Created at: March 8, 2026, 3:14 p.m.