Triple
T23891359
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New Frankfurt |
E600777
|
entity |
| Predicate | kitchenDesigner |
P89588
|
FINISHED |
| Object | Margarete Schütte-Lihotzky |
—
|
NE NERFINISHED |
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: Margarete Schütte-Lihotzky | Statement: [New Frankfurt, kitchenDesigner, Margarete Schütte-Lihotzky]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: kitchenDesigner Context triple: [New Frankfurt, kitchenDesigner, Margarete Schütte-Lihotzky]
-
A.
designConsultant
Indicates that one entity serves as a design consultant, providing expert design advice or services, to another entity.
-
B.
restaurantDesignedBy
Indicates that a restaurant was created or planned by a particular designer or architect.
-
C.
interiorDecoratedBy
chosen
Indicates that the interior of a space or structure has been designed or decorated by a specific agent or entity.
-
D.
designerType
Indicates the specific kind or category of designer role associated with an entity.
-
E.
designIntent
Indicates the underlying purpose, rationale, or functional goal that guided the creation or configuration of something.
- 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_69e295341ac0819080647f2908af793c |
completed | April 17, 2026, 8:16 p.m. |
| NER | Named-entity recognition | batch_69f1cd036dd48190be508063b18762a4 |
completed | April 29, 2026, 9:18 a.m. |
| PD | Predicate disambiguation | batch_69f1614e24b48190a1c8fb5b7c75ee0f |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 8:25 p.m.