Triple
T5103419
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Don River region |
E115032
|
entity |
| Predicate | hasLanguageDuringConflict |
P10179
|
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: [Don River region, hasLanguageDuringConflict, Russian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLanguageDuringConflict Context triple: [Don River region, hasLanguageDuringConflict, Russian]
-
A.
hasLanguageOfSurroundingCountries
Indicates that an entity uses or includes the languages commonly spoken in the countries that geographically surround it.
-
B.
combatantLanguage
chosen
Indicates the language used by a combatant in a conflict or competitive interaction.
-
C.
hasNotableLanguageWithOfficialStatusIn
Indicates that a language holds an officially recognized and notable status within a specified jurisdiction or region.
-
D.
hasRepresentativeLanguage
Indicates that an entity is associated with a language that serves as its primary or officially recognized means of representation or communication.
-
E.
hasMajorityLanguageHistorically
Indicates that a particular language has historically been the predominant or majority language within a given entity or 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_69bd4440b3348190be1251fd8b7951f1 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd7588c1cc81909d380f91ee214808 |
completed | March 20, 2026, 4:27 p.m. |
| PD | Predicate disambiguation | batch_69bd715e06808190931934dc9930f997 |
completed | March 20, 2026, 4:10 p.m. |
Created at: March 20, 2026, 1:41 p.m.