Triple
T24950867
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Round Square |
E624331
|
entity |
| Predicate | hasCommonLanguageOfLocation |
P24056
|
FINISHED |
| Object | Russian |
—
|
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: Russian | Statement: [Round Square, hasCommonLanguageOfLocation, Russian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCommonLanguageOfLocation Context triple: [Round Square, hasCommonLanguageOfLocation, Russian]
-
A.
hasCommonTranslationLanguage
Indicates that two entities share at least one language into which both can be or have been translated.
-
B.
hasLanguageOfSurroundingCountries
Indicates that an entity uses or includes the languages commonly spoken in the countries that geographically surround it.
-
C.
hasPrimaryLanguageNearby
Indicates that an entity is associated with a primary language that is predominantly used or present in its immediate geographic or contextual vicinity.
-
D.
isLinguaFrancaOf
chosen
Indicates that a language serves as a common medium of communication between speakers of different native languages within a particular region, community, or context.
-
E.
hasSecondaryLanguageNearby
Indicates that an entity has at least one secondary language present or used in its immediate vicinity or surrounding context.
- 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_69e2ff22e4c48190a0444b5a044f14e8 |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f67257b0448190a13011af81c81449 |
completed | May 2, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69f66ec3d3d48190ab2f2b71939e572e |
completed | May 2, 2026, 9:38 p.m. |
Created at: April 18, 2026, 5:56 a.m.