Triple
T17709799
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Syretsko–Pecherska line |
E441532
|
entity |
| Predicate | hasTerminus |
P388
|
FINISHED |
| Object | Chervony Khutir |
—
|
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: Chervony Khutir | Statement: [Syretsko–Pecherska line, hasTerminus, Chervony Khutir]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chervony Khutir Context triple: [Syretsko–Pecherska line, hasTerminus, Chervony Khutir]
-
A.
Chervonyi Khutir
chosen
Chervonyi Khutir is a metro station on the Kyiv Metro system in Ukraine.
-
B.
Zavrazhye
Zavrazhye is a rural locality in Russia best known as the birthplace of renowned film director Andrei Tarkovsky.
-
C.
Medzhybizh
Medzhybizh is a historic town in western Ukraine best known as a major center of early Hasidic Judaism and the longtime home of the Baal Shem Tov.
-
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.
Horodyshche
Horodyshche is a town in central Ukraine known as a local administrative and cultural center within the Cherkasy 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_69d8b9ea20b48190ace88bb46b01e6a9 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e4729a9a9c81908d65ff0bda12c961 |
completed | April 19, 2026, 6:13 a.m. |
Created at: April 10, 2026, 10:05 a.m.