Triple
T26439325
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | portraits of Lord Byron |
E665041
|
entity |
| Predicate | hasDepictedPersonNationality |
P15072
|
FINISHED |
| Object | British |
—
|
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: British | Statement: [portraits of Lord Byron, hasDepictedPersonNationality, British]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDepictedPersonNationality Context triple: [portraits of Lord Byron, hasDepictedPersonNationality, British]
-
A.
depictsNationality
chosen
Indicates that one entity visually represents or portrays the nationality or national identity of another entity.
-
B.
hasDirectorNationality
Indicates that the nationality of a director is associated with a given entity (such as a film, organization, or work).
-
C.
nationalityOfPersonReferredTo
Indicates that one entity is the country or nationality associated with the person referenced by the other entity.
-
D.
portrayedByCountryOfCitizenship
Indicates that the subject is depicted or represented by an individual whose country of citizenship is the specified country.
-
E.
depictsNotablePerson
Indicates that one entity visually represents or portrays a person who is considered notable or significant.
- 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_69ee883c851881909e2ab04efbb3c5fe |
completed | April 26, 2026, 9:48 p.m. |
| NER | Named-entity recognition | batch_69f6ffbad8848190867c2988c0ceb84f |
completed | May 3, 2026, 7:56 a.m. |
| PD | Predicate disambiguation | batch_69f6fc53f4f881908dcc698687bbb64d |
completed | May 3, 2026, 7:42 a.m. |
Created at: April 26, 2026, 11:56 p.m.