Triple
T850834
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bern |
E18380
|
entity |
| Predicate | twinCity |
P1072
|
FINISHED |
| Object | Kazan |
E35521
|
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: Kazan | Statement: [Bern, twinCity, Kazan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kazan Context triple: [Bern, twinCity, Kazan]
-
A.
Kazan
chosen
Kazan is a major city in western Russia and the capital of the Republic of Tatarstan, known for its rich Tatar-Russian cultural heritage and historic Kremlin.
-
B.
Samara
Samara is a major Russian city on the Volga River known as an important industrial, cultural, and transportation hub.
-
C.
Yekaterinburg
Yekaterinburg is a major industrial and cultural city in Russia’s Ural region, historically known as the site of the execution of the last Russian tsar, Nicholas II, and his family.
-
D.
Ulyanov
Ulyanov is the Russian surname of Vladimir Lenin, the revolutionary leader and founder of the Soviet state.
-
E.
Grozny
Grozny is the capital and largest city of the Chechen Republic in southwestern Russia, known for its turbulent recent history and extensive post-war reconstruction.
- 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_69a4938b04208190b82e1df6b572c548 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ac215194819099e6bc1b5df58fb3 |
completed | March 1, 2026, 9:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac939b0fbc8190a205a5033568ba9c |
completed | March 7, 2026, 9:07 p.m. |
Created at: March 1, 2026, 7:38 p.m.