Triple
T28892059
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Katwe |
E732725
|
entity |
| Predicate | realWorldSettingFor |
P54861
|
FINISHED |
| Object | Queen of Katwe (film) |
—
|
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: Queen of Katwe (film) | Statement: [Katwe, realWorldSettingFor, Queen of Katwe (film)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: realWorldSettingFor Context triple: [Katwe, realWorldSettingFor, Queen of Katwe (film)]
-
A.
realWorldParallel
Indicates that one entity has a counterpart, analogy, or directly corresponding situation in the real world relative to another entity.
-
B.
soldInRealWorld
Indicates that the item or product is actually sold or available for purchase in the physical, real-world marketplace.
-
C.
portrayedInSetting
chosen
Indicates that an entity is depicted or represented within a particular setting, environment, or context.
-
D.
realWorldStudio
Indicates a relationship where an entity is associated with, produced by, or taking place in a real-world studio environment (as opposed to virtual or simulated settings).
-
E.
realWorldNote
Indicates that an entity is associated with a note or annotation that applies specifically to real-world context or usage, rather than abstract or theoretical information.
- 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_69f05b08c2008190ac426a035a2ed66d |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69f65b14512c8190a40e70319dcc54cd |
completed | May 2, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69f659d02f1c8190831758ac52bb54e4 |
completed | May 2, 2026, 8:08 p.m. |
Created at: April 28, 2026, 7:56 a.m.