Triple
T24678435
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dr. Jaquith |
E611055
|
entity |
| Predicate | nationalityInferredFromActor |
P36925
|
FINISHED |
| Object | American |
—
|
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: American | Statement: [Dr. Jaquith, nationalityInferredFromActor, American]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nationalityInferredFromActor Context triple: [Dr. Jaquith, nationalityInferredFromActor, American]
-
A.
nationalityOfActor
chosen
Indicates that a specified nationality is associated with, or belongs to, a particular actor.
-
B.
nationalityOfPersonReferredTo
Indicates that one entity is the country or nationality associated with the person referenced by the other entity.
-
C.
portrayalNationalityOfActor
Indicates that an actor portrays a character of a specified nationality in a performance or work.
-
D.
hasDirectorNationality
Indicates that the nationality of a director is associated with a given entity (such as a film, organization, or work).
-
E.
nationalityInferredFromSetting
Indicates that an entity’s nationality is deduced indirectly from contextual clues about its location or setting rather than stated explicitly.
- 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_69e2c4d5c2dc8190ac857dea25ec6ce9 |
completed | April 17, 2026, 11:40 p.m. |
| NER | Named-entity recognition | batch_69f41011d8048190be70329ba0bfb7c7 |
completed | May 1, 2026, 2:29 a.m. |
| PD | Predicate disambiguation | batch_69f40ed9d47881909fcfc0d04e8d074a |
completed | May 1, 2026, 2:24 a.m. |
Created at: April 18, 2026, 3:07 a.m.