Triple
T19896113
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | southern front of the Russo-Ukrainian War |
E478156
|
entity |
| Predicate | includesCity |
P3207
|
FINISHED |
| Object | Berdyansk |
—
|
NE NERFINISHED |
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: Berdyansk | Statement: [southern front of the Russo-Ukrainian War, includesCity, Berdyansk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Berdyansk Context triple: [southern front of the Russo-Ukrainian War, includesCity, Berdyansk]
-
A.
Berdyansk
chosen
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.
-
B.
Rostov-on-Don
Rostov-on-Don is a major port city in southern Russia, located on the Don River near the Sea of Azov and serving as an important administrative, cultural, and industrial center of the region.
-
C.
Novocherkassk
Novocherkassk is a historic city in Russia’s Rostov Oblast that served as a key Cossack and military administrative center.
-
D.
Krasnovodsk
Krasnovodsk, now known as Türkmenbaşy, is a key port city on the eastern shore of the Caspian Sea in western Turkmenistan.
-
E.
Zheleznovodsk
Zheleznovodsk is a spa town in Russia’s Stavropol Krai, known for its mineral springs and health resorts in the Caucasus region.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e520682081909892916424699bd5 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6593dba78819082c8b80e65246171 |
completed | April 20, 2026, 4:50 p.m. |
Created at: April 10, 2026, 1:52 p.m.