Triple
T24652350
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | U2 |
E610285
|
entity |
| Predicate | hasDesignLanguageCharacterizedBy |
P90386
|
FINISHED |
| Object | bold typography |
—
|
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: bold typography | Statement: [U2, hasDesignLanguageCharacterizedBy, bold typography]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDesignLanguageCharacterizedBy Context triple: [U2, hasDesignLanguageCharacterizedBy, bold typography]
-
A.
hasDesignLanguage
chosen
Indicates that one entity employs, follows, or is characterized by the design language specified by another entity.
-
B.
introducedDesignLanguage
Indicates that an entity initiated or brought a particular design language into use or public awareness.
-
C.
primaryLanguageOfDesignTradition
Indicates the main natural language used within a particular design tradition for its communication, documentation, and conceptual development.
-
D.
languageCharacterizedBy
Indicates that a language is defined or distinguished by a particular feature, property, or characteristic.
-
E.
isDesignedAs
Indicates that something has been intentionally created or configured to serve as or function in the role of something else.
- 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_69e2c4d350a481909170482bc2ce6af9 |
completed | April 17, 2026, 11:40 p.m. |
| NER | Named-entity recognition | batch_69f422aee0408190899efe7e24ef2b40 |
completed | May 1, 2026, 3:49 a.m. |
| PD | Predicate disambiguation | batch_69f420e92cc88190a803aecdae78a051 |
completed | May 1, 2026, 3:41 a.m. |
Created at: April 18, 2026, 2:34 a.m.