Triple
T23666606
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amri Karbi |
E584594
|
entity |
| Predicate | hasPhonologicalRelationWith |
P8038
|
FINISHED |
| Object | other Karbi dialects |
—
|
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: other Karbi dialects | Statement: [Amri Karbi, hasPhonologicalRelationWith, other Karbi dialects]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPhonologicalRelationWith Context triple: [Amri Karbi, hasPhonologicalRelationWith, other Karbi dialects]
-
A.
phonologyRelation
Indicates a relationship between linguistic elements based on their phonological properties, such as sound patterns, features, or structures.
-
B.
hasPhonologicalBasisFor
Indicates that one entity serves as the phonological source, motivation, or foundation for another entity.
-
C.
hasPhonologicalSimilarityTo
chosen
Indicates that two linguistic elements share similar sound patterns or phonological features.
-
D.
hasTypologicalRelation
Indicates a relationship where two linguistic entities are connected based on shared structural or typological features, such as word order, morphology, or phonological patterns.
-
E.
linguisticallyRelatedTo
Indicates that two entities are connected through a linguistic relationship, such as sharing a common language, origin, structure, or other language-based association.
- 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_69e24901421881908c17a5293bdd4a8e |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b40c48088190a61e9a73919bace5 |
completed | April 29, 2026, 7:32 a.m. |
| PD | Predicate disambiguation | batch_69f118dd13008190a8799b4e9cadbd79 |
completed | April 28, 2026, 8:30 p.m. |
Created at: April 17, 2026, 6:50 p.m.