Triple
T20126575
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ariyo Atthangiko Maggo |
E490772
|
entity |
| Predicate | hasEnglishComponent |
P138780
|
FINISHED |
| Object | Right View |
—
|
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: Right View | Statement: [Ariyo Atthangiko Maggo, hasEnglishComponent, Right View]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEnglishComponent Context triple: [Ariyo Atthangiko Maggo, hasEnglishComponent, Right View]
-
A.
hasEnglishReception
Indicates that something has been received, interpreted, or responded to within an English-speaking context.
-
B.
hasEnglishEdition
Indicates that one entity has a version or edition of itself that is produced or available in the English language.
-
C.
hasEnglishName
Indicates that an entity is associated with a name expressed in the English language.
-
D.
hasLanguageOfStudy
Indicates that an entity studies or is engaged in learning a particular language.
-
E.
alsoUsesLanguageOfInstruction
Indicates that an entity, in addition to its primary language, uses the same language that is designated as the language of instruction in a given context.
- 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_69da62651a0c8190a3e05e95e056a66b |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e66743494c81908e63a5efca3aa3ea |
completed | April 20, 2026, 5:49 p.m. |
| PD | Predicate disambiguation | batch_69e54cfb0d0081908e789b9b57e96668 |
completed | April 19, 2026, 9:45 p.m. |
| PDg | Predicate description generation | batch_69e54fc2bc3c819088c33cd263303433 |
completed | April 19, 2026, 9:57 p.m. |
Created at: April 11, 2026, 11:31 p.m.