Triple
T11592523
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sevastopolskaya |
E274918
|
entity |
| Predicate | hasTransferTo |
P17241
|
FINISHED |
| Object | Kakhovskaya |
E229210
|
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: Kakhovskaya | Statement: [Sevastopolskaya, hasTransferTo, Kakhovskaya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kakhovskaya Context triple: [Sevastopolskaya, hasTransferTo, Kakhovskaya]
-
A.
Kakhovskaya
chosen
Kakhovskaya is a Moscow Metro station that serves as part of the city’s Big Circle Line.
-
B.
Sievierodonetsk
Sievierodonetsk is an industrial city in eastern Ukraine that became a focal point of intense fighting during the war in the Donbas and the 2022 Russian invasion.
-
C.
Baturyn
Baturyn is a historic town in northern Ukraine that served as a major political and military center of the Cossack Hetmanate in the 17th–18th centuries.
-
D.
Voykovskaya
Voykovskaya is a Moscow Metro station serving the Zamoskvoretskaya Line in the northern part of the city.
-
E.
Krymsky Val
Krymsky Val is a notable street in central Moscow, Russia, known for its proximity to Gorky Park and several major cultural institutions.
- 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_69d6aae6b14c81908dc5a74bad7591f9 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8946594348190935106132fd18028 |
completed | April 10, 2026, 6:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e714634b308190bdcb761f8b6712e7 |
completed | April 21, 2026, 6:08 a.m. |
Created at: April 8, 2026, 9:38 p.m.