Triple
T24646439
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shkhara Glacier |
E610123
|
entity |
| Predicate | languageOfToponymRegion |
P24399
|
FINISHED |
| Object | Georgian |
—
|
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: Georgian | Statement: [Shkhara Glacier, languageOfToponymRegion, Georgian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfToponymRegion Context triple: [Shkhara Glacier, languageOfToponymRegion, Georgian]
-
A.
hasLanguageOfToponym
chosen
Indicates that a place name (toponym) is expressed in or associated with a particular language.
-
B.
etymologyRegion
Indicates the geographic region from which a word’s etymological origin or historical linguistic development is derived.
-
C.
languageOfHistoricName
Indicates the language in which a historic or former name of an entity is expressed.
-
D.
regionOfMajorLanguage
Indicates the geographic region where a particular language is predominantly spoken or holds major usage.
-
E.
regionLanguage
Indicates that a particular language is used or officially recognized within a specific geographic region.
- 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_69e2c4d350a481909170482bc2ce6af9 |
completed | April 17, 2026, 11:40 p.m. |
| NER | Named-entity recognition | batch_69f41011d8048190be70329ba0bfb7c7 |
completed | May 1, 2026, 2:29 a.m. |
| PD | Predicate disambiguation | batch_69f40ed9d47881909fcfc0d04e8d074a |
completed | May 1, 2026, 2:24 a.m. |
Created at: April 18, 2026, 2:33 a.m.