Triple
T17604393
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Martin Baltimore |
E428787
|
entity |
| Predicate | nationalityOfDesign |
P35634
|
FINISHED |
| Object | American |
—
|
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: American | Statement: [Martin Baltimore, nationalityOfDesign, American]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nationalityOfDesign Context triple: [Martin Baltimore, nationalityOfDesign, American]
-
A.
designerNationality
chosen
Indicates that a designer has a specific national or country affiliation.
-
B.
countryOfDesignActivity
Indicates the country in which the design-related activity associated with an entity takes place or is carried out.
-
C.
designationCountry
Indicates the country that officially assigns or confers a particular status, title, or designation on an entity.
-
D.
brandNationality
Indicates that a brand is associated with or originates from a particular country or nationality.
-
E.
nationalityOfPersonReferredTo
Indicates that one entity is the country or nationality associated with the person referenced by the other entity.
- 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_69d889e1c6148190ba76241e74688f8b |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e46c4b4ee88190827ea28b99ca6f33 |
completed | April 19, 2026, 5:46 a.m. |
| PD | Predicate disambiguation | batch_69e3cdd7da34819099bc9481c5a79bab |
completed | April 18, 2026, 6:30 p.m. |
Created at: April 10, 2026, 5:51 a.m.