Triple
T4608919
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kamensky |
E100505
|
entity |
| Predicate | hasFeminineForm |
P1613
|
FINISHED |
| Object | Kamenskaya |
E483972
|
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: Kamenskaya | Statement: [Kamensky, hasFeminineForm, Kamenskaya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kamenskaya Context triple: [Kamensky, hasFeminineForm, Kamenskaya]
-
A.
Khoroshevskaya
Khoroshevskaya is a Moscow Metro station located on the Big Circle Line, serving the Khoroshyovsky District of the city.
-
B.
Krasnopresnenskaya
Krasnopresnenskaya is a Moscow Metro station on the city’s circular Koltsevaya Line, known for its deep-level construction and Soviet-era architectural design.
-
C.
Paveletskaya
Paveletskaya is a Moscow Metro station named after the nearby Paveletsky railway terminal, serving as a key transport hub in the city’s network.
-
D.
Kamenskiy
chosen
Kamenskiy is a Slavic surname, commonly transliterated from Russian or related languages, borne by various individuals across Eastern Europe and the former Soviet Union.
-
E.
Karamyshevskaya
Karamyshevskaya is a metro station on Moscow’s Big Circle Line, serving the Khoroshyovo-Mnyovniki area of the city.
- 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_69bd43cce1e08190a07d53af6a9b6c24 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd599f08d88190ad4bed8bafb592cd |
completed | March 20, 2026, 2:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be9c36bfb081908d02a52c6e3affa1 |
completed | March 21, 2026, 1:25 p.m. |
Created at: March 20, 2026, 1:12 p.m.