Triple
T9126287
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Burmese nationalism |
E218974
|
entity |
| Predicate | linkedToLanguage |
P87230
|
FINISHED |
| Object | Burmese language |
—
|
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: Burmese language | Statement: [Burmese nationalism, linkedToLanguage, Burmese language]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: linkedToLanguage Context triple: [Burmese nationalism, linkedToLanguage, Burmese language]
-
A.
linguisticallyRelatedTo
Indicates that two entities are connected through a linguistic relationship, such as sharing a common language, origin, structure, or other language-based association.
-
B.
closelyAssociatedLanguage
Indicates that one language is closely connected to another, such as through frequent co-use, mutual influence, or strong cultural or regional association.
-
C.
influencedLanguage
Indicates that one language has had an effect on the development, structure, or usage of another language.
-
D.
associatedLanguageRegulator
Indicates that one entity serves as the official or recognized regulatory body responsible for overseeing, standardizing, or managing the language associated with another entity.
-
E.
languageCodeRelation
Indicates a relationship where one entity is associated with, identified by, or mapped to a specific language code of another entity.
- 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_69ca83debfc0819095800583e97ab10f |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cca8c93d3c8190b003b2b1af2003b2 |
completed | April 1, 2026, 5:10 a.m. |
| PD | Predicate disambiguation | batch_69cc66003e3c819091e1e42c9cf7c781 |
completed | April 1, 2026, 12:25 a.m. |
| PDg | Predicate description generation | batch_69cc6a3c78388190a7436acc0e44ff55 |
completed | April 1, 2026, 12:43 a.m. |
Created at: March 30, 2026, 7:18 p.m.