Triple
T13843722
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nizhegorodskaya |
E332735
|
entity |
| Predicate | hasNameInLanguage |
P15
|
FINISHED |
| Object | Nizhegorodskaya |
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: Nizhegorodskaya | Statement: [Nizhegorodskaya, hasNameInLanguage, Nizhegorodskaya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nizhegorodskaya Context triple: [Nizhegorodskaya, hasNameInLanguage, Nizhegorodskaya]
-
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.
Nizhny Novgorod Oblast
Nizhny Novgorod Oblast is a federal subject of central Russia known for its major industrial centers, historical cities, and strategic location along the Volga River.
-
C.
Tambov
Tambov is a city in western Russia known as an administrative, cultural, and industrial center of the Tambov Oblast.
-
D.
Oryol
Oryol was a notable warship of the Imperial Russian Navy, recognized for its role in Russia’s early modern naval history.
-
E.
Ryazan Oblast
Ryazan Oblast is a federal subject of central Russia known for its historic cities, agricultural landscapes, and location along the Oka River southeast of Moscow.
- 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_69f7b8f87c188190b90faf7678cb9ad4 |
completed | May 3, 2026, 9:07 p.m. |
Created at: April 9, 2026, 10:13 p.m.