Triple
T36155154
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Irkeshtam Pass |
E1045709
|
entity |
| Predicate | languageAtBorder |
P194242
|
FINISHED |
| Object | Kyrgyz |
—
|
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: Kyrgyz | Statement: [Irkeshtam Pass, languageAtBorder, Kyrgyz]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageAtBorder Context triple: [Irkeshtam Pass, languageAtBorder, Kyrgyz]
-
A.
languageAlongBorder
Indicates that a particular language is spoken or prevalent along the border between two regions or entities.
-
B.
languageBorderInvolved
Indicates that a situation, event, or relationship involves or is affected by a boundary between different languages or linguistic communities.
-
C.
officialLanguageAtCrossing
chosen
Indicates that a specified language is officially used or recognized at a particular border crossing.
-
D.
languageOfSurroundingCountry
Indicates that a language is the primary or commonly used language in the country surrounding a given place or region.
-
E.
borderDialectOf
Indicates a dialect that is spoken in a border area and is linguistically associated with or derived from a particular neighboring language or dialect.
- 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_69f76e38903c8190a52887620f90aabe |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a01185c46f0819089b4a2ad3c3e2f33 |
completed | May 10, 2026, 11:44 p.m. |
| PD | Predicate disambiguation | batch_6a0117e19e008190870663dd45084416 |
completed | May 10, 2026, 11:42 p.m. |
Created at: May 3, 2026, 4:08 p.m.