Triple
T24374329
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Circus (1928 film short) |
E614424
|
entity |
| Predicate | hasCountryOfLeadActorBirth |
P155955
|
FINISHED |
| Object | Australia |
—
|
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: Australia | Statement: [The Circus (1928 film short), hasCountryOfLeadActorBirth, Australia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCountryOfLeadActorBirth Context triple: [The Circus (1928 film short), hasCountryOfLeadActorBirth, Australia]
-
A.
hasDirectorNationality
Indicates that the nationality of a director is associated with a given entity (such as a film, organization, or work).
-
B.
nationalityOfActor
Indicates that a specified nationality is associated with, or belongs to, a particular actor.
-
C.
representedCountryAtOscars
Indicates that an entity served as the official representative of a particular country at the Academy Awards (Oscars) in a given year or category.
-
D.
hasCinematographerNationality
Indicates that a cinematographer is associated with a specific nationality.
-
E.
countryOf
Indicates that one entity is the country to which another entity belongs, is located in, or is associated with.
- F. None of above. chosen
Provenance (4 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_69e2d7e1e010819098b95eb3f905943d |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f293d67404819091281523ef12b9b5 |
completed | April 29, 2026, 11:27 p.m. |
| PD | Predicate disambiguation | batch_69f287bb1b2c81909c2e7fcc392ad143 |
completed | April 29, 2026, 10:35 p.m. |
| PDg | Predicate description generation | batch_69f28f4d978c81908310c01def2514cc |
completed | April 29, 2026, 11:07 p.m. |
Created at: April 18, 2026, 2:02 a.m.