Triple
T12337129
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chertanovskaya |
E294115
|
entity |
| Predicate | hasAdjacentStation |
P231
|
FINISHED |
| Object | Varshavskaya |
E258163
|
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: Varshavskaya | Statement: [Chertanovskaya, hasAdjacentStation, Varshavskaya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Varshavskaya Context triple: [Chertanovskaya, hasAdjacentStation, Varshavskaya]
-
A.
Varshavskaya
chosen
Varshavskaya is a Moscow Metro station on the Big Circle Line serving the southern part of the city.
-
B.
Nakhimovsky
Nakhimovsky is a Russian surname derived from the name Nakhimov, commonly used in Slavic-speaking regions.
-
C.
Buninskaya Alleya
Buninskaya Alleya is a Moscow Metro station serving as the southern endpoint of the Butovskaya Line in the Butovo district of Moscow, Russia.
-
D.
Rozhdestvenskaya Street
Rozhdestvenskaya Street is a historic and architecturally significant street in Nizhny Novgorod, Russia, known for its well-preserved merchant buildings and cultural landmarks.
-
E.
Sumskaya Street
Sumskaya Street is a central thoroughfare in Kharkiv, Ukraine, known for its historic architecture, cultural landmarks, and role as one of the city’s main streets.
- 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_69d6ab6ae0dc8190b1522a9c1c55c114 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f6683e881908920e1fee02a14e3 |
completed | April 10, 2026, 6:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff01ce8f988190b503af0cd5f2a97e |
completed | May 9, 2026, 9:43 a.m. |
Created at: April 8, 2026, 9:53 p.m.