Triple
T21597533
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Horizons |
E532940
|
entity |
| Predicate | programmingScope |
P89488
|
FINISHED |
| Object | films from around the world |
—
|
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: films from around the world | Statement: [Horizons, programmingScope, films from around the world]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: programmingScope Context triple: [Horizons, programmingScope, films from around the world]
-
A.
programmingFocus
Indicates a relationship where an entity’s primary attention, effort, or specialization is directed toward a particular area or aspect of programming.
-
B.
programmaticScope
chosen
Indicates the defined range or boundary within which a program, initiative, or set of actions is intended to operate or have effect.
-
C.
programmingLanguage
Indicates that one entity is a programming language used to create, control, or interact with the other entity.
-
D.
programmingIncludes
Indicates that one programming-related entity contains, incorporates, or makes use of another as a part, feature, or component.
-
E.
programming
Indicates that an entity writes, develops, or modifies software or code, typically using a programming language to create or control computer programs.
- 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_69e0c46364608190a337dc8720dc2a35 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69eefae20c8881909c5354313d06183a |
completed | April 27, 2026, 5:57 a.m. |
| PD | Predicate disambiguation | batch_69e632109d048190b4ac3f14fe48d1a0 |
completed | April 20, 2026, 2:02 p.m. |
Created at: April 16, 2026, 6:32 p.m.