Triple
T26894464
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saraikis |
E677862
|
entity |
| Predicate | macroLinguisticGroup |
P27696
|
FINISHED |
| Object | Lahnda |
—
|
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: Lahnda | Statement: [Saraikis, macroLinguisticGroup, Lahnda]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: macroLinguisticGroup Context triple: [Saraikis, macroLinguisticGroup, Lahnda]
-
A.
macrolanguageGrouping
chosen
Indicates that one language is classified as part of a broader macrolanguage grouping that encompasses multiple closely related language varieties.
-
B.
arealLinguisticGroup
Indicates a relationship where languages are grouped together based on shared features arising from geographic proximity and contact, rather than common genetic origin.
-
C.
majorLanguageGroupOf
Indicates that one language group is the primary or dominant linguistic classification to which another language or set of languages belongs.
-
D.
macrolanguageMemberOf
Indicates that a language variety is classified as a member of a larger macrolanguage grouping.
-
E.
linguisticSubgroup
Indicates that one linguistic group forms a subordinate or specialized subset within a larger linguistic group or family.
- 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_69eee9befee48190a26f214faa867be7 |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69f61f6ac6ac8190be96a4211305dbbe |
completed | May 2, 2026, 3:59 p.m. |
| PD | Predicate disambiguation | batch_69f611af72ac819094598dd2530d7411 |
completed | May 2, 2026, 3:01 p.m. |
Created at: April 27, 2026, 5:47 a.m.