Triple
T3077146
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Southern Russia |
E64164
|
entity |
| Predicate | hasMajorCity |
P316
|
FINISHED |
| Object | Astrakhan |
E380061
|
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: Astrakhan | Statement: [Southern Russia, hasMajorCity, Astrakhan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Astrakhan Context triple: [Southern Russia, hasMajorCity, Astrakhan]
-
A.
Astrakhan
chosen
Astrakhan is a historic Russian city near the Caspian Sea, known as a key Volga River port and gateway to the Volga Delta region.
-
B.
Orenburg
Orenburg is a major city in southwestern Russia near the Ural River, historically significant as a frontier fortress and administrative center linking European Russia with Central Asia.
-
C.
Cheboksary
Cheboksary is a major city on the Volga River in western Russia and the capital of the Chuvash Republic.
-
D.
Berdyansk
Berdyansk is a port city in southeastern Ukraine on the northern coast of the Sea of Azov, known for its maritime trade, beaches, and resort facilities.
-
E.
Kamyshin
Kamyshin is a significant industrial and river port city on the Volga River in southwestern Russia.
- 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_69ad857a8aec8190bfdfd9c14554ac5a |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada1a6f6148190ae5cd6e45eda9006 |
completed | March 8, 2026, 4:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be8195518081908f4938032218e118 |
completed | March 21, 2026, 11:31 a.m. |
Created at: March 8, 2026, 3:02 p.m.