Triple
T30006193
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Little Brother |
E762326
|
entity |
| Predicate | hasActorNationality |
P36925
|
FINISHED |
| Object | Australian (for lead actress Enid Bennett) |
—
|
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: Australian (for lead actress Enid Bennett) | Statement: [The Little Brother, hasActorNationality, Australian (for lead actress Enid Bennett)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasActorNationality Context triple: [The Little Brother, hasActorNationality, Australian (for lead actress Enid Bennett)]
-
A.
hasDirectorNationality
Indicates that the nationality of a director is associated with a given entity (such as a film, organization, or work).
-
B.
hasCrewNationality
Indicates that the members of a crew possess a specified nationality.
-
C.
nationalityOfActor
chosen
Indicates that a specified nationality is associated with, or belongs to, a particular actor.
-
D.
hasCinematographerNationality
Indicates that a cinematographer is associated with a specific nationality.
-
E.
hasParticipantNationality
Indicates that a participant in an event, activity, or relation has a specific nationality.
- 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_69f2246a47ac81909cf5213053687ffc |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f71422adac8190a5ceb32dcf820833 |
completed | May 3, 2026, 9:23 a.m. |
| PD | Predicate disambiguation | batch_69f712764d2c819081b64b27e5de4a13 |
completed | May 3, 2026, 9:16 a.m. |
Created at: April 29, 2026, 6:42 p.m.