Triple
T24710954
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Colonel Redl |
E612023
|
entity |
| Predicate | representedCountryForOscar |
P76394
|
FINISHED |
| Object | Hungary |
—
|
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: Hungary | Statement: [Colonel Redl, representedCountryForOscar, Hungary]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: representedCountryForOscar Context triple: [Colonel Redl, representedCountryForOscar, Hungary]
-
A.
representedCountryAtOscars
chosen
Indicates that an entity served as the official representative of a particular country at the Academy Awards (Oscars) in a given year or category.
-
B.
bestPictureWinnerCountry
Indicates the country associated with the film that won the Best Picture award in a given year or context.
-
C.
nationalityOfActor
Indicates that a specified nationality is associated with, or belongs to, a particular actor.
-
D.
hasCountryOfLeadActorBirth
Indicates that the relationship specifies the country where the lead actor in a work was born.
-
E.
supportingActorAwardRecipient
Indicates that an entity has received an award specifically for a supporting acting role in a performance or production.
- 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_69e2c4d9c24c8190a3712d74327f0c6e |
completed | April 17, 2026, 11:40 p.m. |
| NER | Named-entity recognition | batch_69f60c3b09488190ade1b69ff7f0df0e |
completed | May 2, 2026, 2:37 p.m. |
| PD | Predicate disambiguation | batch_69f60b8461ac81908c5bd3d73eed59f4 |
completed | May 2, 2026, 2:34 p.m. |
Created at: April 18, 2026, 3:24 a.m.