Triple
T5110775
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | B. J. Novak as Robert B. Sherman |
E115207
|
entity |
| Predicate | portraysNationality |
P32391
|
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: [B. J. Novak as Robert B. Sherman, portraysNationality, American]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portraysNationality Context triple: [B. J. Novak as Robert B. Sherman, portraysNationality, American]
-
A.
portrayalNationalityOfActor
chosen
Indicates that an actor portrays a character of a specified nationality in a performance or work.
-
B.
depictsNationality
Indicates that one entity visually represents or portrays the nationality or national identity of another entity.
-
C.
nationalityOfActor
Indicates that a specified nationality is associated with, or belongs to, a particular actor.
-
D.
hasDirectorNationality
Indicates that the nationality of a director is associated with a given entity (such as a film, organization, or work).
-
E.
nationalityInStory
Indicates that a character or entity in a narrative is associated with a particular nationality within the context of that story.
- 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_69bd4441d1648190a54a533895041987 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd75ad362c8190b9cbded390aaea3c |
completed | March 20, 2026, 4:28 p.m. |
| PD | Predicate disambiguation | batch_69bd715fe3a8819087d3065adddba515 |
completed | March 20, 2026, 4:10 p.m. |
Created at: March 20, 2026, 1:41 p.m.