Triple
T19156295
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lypky |
E468934
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | Pechersk |
—
|
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: Pechersk | Statement: [Lypky, partOf, Pechersk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pechersk Context triple: [Lypky, partOf, Pechersk]
-
A.
Pechersky
Pechersky is a surname most notably associated with Alexander Pechersky, a leader of the 1943 Sobibor extermination camp uprising during the Holocaust.
-
B.
Pecherska
chosen
Pecherska is a Kyiv Metro station on the Syretsko–Pecherska line serving the Pechersk district of Ukraine’s capital.
-
C.
Usvyaty
Usvyaty is an urban-type settlement in Pskov Oblast, Russia, known as a local administrative and cultural center near the borders with Belarus and Latvia.
-
D.
Sviatoshyn
Sviatoshyn is a residential neighborhood in Kyiv, Ukraine, known for its location along the city’s metro system and its mix of Soviet-era housing and green spaces.
-
E.
Kievskaya
Kievskaya is a prominent Moscow Metro station complex known for its ornate, Ukrainian-themed architecture and role as a major transfer hub.
- 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_69d8dd084ff48190ac0f8c46ee722629 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5eeb9cf9081908b17073755e83554 |
completed | April 20, 2026, 9:15 a.m. |
Created at: April 10, 2026, 12:06 p.m.