Triple
T13843723
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nizhegorodskaya |
E332735
|
entity |
| Predicate | hasNameInLanguage |
P15
|
FINISHED |
| Object | Нижегородская |
E332735
|
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: Нижегородская | Statement: [Nizhegorodskaya, hasNameInLanguage, Нижегородская]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Нижегородская Context triple: [Nizhegorodskaya, hasNameInLanguage, Нижегородская]
-
A.
Nizhegorodskaya
chosen
Nizhegorodskaya is a Moscow Metro station on the Big Circle Line serving the Nizhegorodsky District in the southeast of the city.
-
B.
Владимирская
Владимирская is a station of the Saint Petersburg Metro in Russia, serving the city’s central area.
-
C.
Тульская
Тульская — это станция Московского метрополитена на Серпуховско-Тимирязевской линии, расположенная в южной части города.
-
D.
Volzhsky
Volzhsky is a major industrial city in southwestern Russia located across the Volga River from Volgograd.
-
E.
Vologda
Vologda is a historic city in northwestern Russia known for its well-preserved wooden architecture, ancient monasteries, and traditional lace-making.
- 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_69d81c5ba13c8190839315f54768acfd |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de02afce788190a74dce4e6a3569fa |
completed | April 14, 2026, 9:02 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7c0ef9e7c8190b96c2b83d04708e1 |
completed | May 3, 2026, 9:41 p.m. |
Created at: April 9, 2026, 10:13 p.m.