Triple
T9711397
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Savoy Restaurant interior, Helsinki |
E235029
|
entity |
| Predicate | hasDesignLanguage |
P90386
|
FINISHED |
| Object | clean lines |
—
|
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: clean lines | Statement: [Savoy Restaurant interior, Helsinki, hasDesignLanguage, clean lines]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDesignLanguage Context triple: [Savoy Restaurant interior, Helsinki, hasDesignLanguage, clean lines]
-
A.
hasDesign
Indicates that one entity possesses, embodies, or is characterized by a particular design associated with another entity.
-
B.
designedWith
Indicates that one entity was created, planned, or developed using another entity as a tool, method, or guiding basis in its design process.
-
C.
languageDesigned
Indicates that one entity created or developed the language used or associated with another entity.
-
D.
primaryLanguageOfDesignTradition
Indicates the main natural language used within a particular design tradition for its communication, documentation, and conceptual development.
-
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. chosen
Provenance (4 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_69ca84cd8fa0819090a5e243ceb37003 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9e0591208190aa57cc9e2aebafb7 |
completed | April 1, 2026, 10:36 p.m. |
| PD | Predicate disambiguation | batch_69cd03bfeca08190924fca43aaa9c10f |
completed | April 1, 2026, 11:38 a.m. |
| PDg | Predicate description generation | batch_69cd06aa8bc88190904be19c8953def8 |
completed | April 1, 2026, 11:51 a.m. |
Created at: March 30, 2026, 8:19 p.m.