Triple
T8166701
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Surzhyk |
E190709
|
entity |
| Predicate | contrastedWith |
P278
|
FINISHED |
| Object | Standard Russian |
E3584
|
NE 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: Standard Russian | Statement: [Surzhyk, contrastedWith, Standard Russian]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Standard Russian Context triple: [Surzhyk, contrastedWith, Standard Russian]
-
A.
Russian language
chosen
Russian is an East Slavic language spoken primarily in Russia and neighboring countries, serving as one of the world's major languages in politics, science, and culture.
-
B.
Russo
Russo is an Italian surname commonly used as a variant of Rossi, often associated with people of Italian heritage.
-
C.
Russin
Russin is a small wine-producing municipality and village located in the canton of Geneva in southwestern Switzerland.
-
D.
The Russian
The Russian is a thriller novel in James Patterson and James O. Born’s Michael Bennett series, in which the NYPD detective hunts a brutal serial killer targeting women across multiple cities.
-
E.
Rus
Rus was a medieval East Slavic cultural and political realm that laid the foundations for the modern nations of Russia, Ukraine, and Belarus.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca82c0ef14819083713f4473dd847c |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb46680fac81908df134df9bf84915 |
completed | March 31, 2026, 3:58 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ccbf4b68288190be7490119d46b242 |
completed | April 1, 2026, 6:46 a.m. |
Created at: March 30, 2026, 5:39 p.m.