Triple
T23131936
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Penza Oblast |
E577191
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object |
Nikolsk
Nikolsk is a small Russian town located in Penza Oblast, known for its traditional glassmaking industry and historical provincial character.
|
E1571495
|
NE FINISHED |
How this triple was built (4 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: Nikolsk | Statement: [Penza Oblast, hasCity, Nikolsk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nikolsk Context triple: [Penza Oblast, hasCity, Nikolsk]
-
A.
Nikolskoye
Nikolskoye is the main and only permanent settlement on Russia’s remote Commander Islands in the Bering Sea.
-
B.
Nikolskoye
Nikolskoye is a town in northwestern Russia known as part of the Saint Petersburg metropolitan area in Leningrad Oblast.
-
C.
Nikiforovo
Nikiforovo is a village located in the mountainous Mavrovo region of North Macedonia, known for its proximity to Mavrovo National Park and Lake Mavrovo.
-
D.
Nagurskoye
Nagurskoye is a small Russian military and research settlement located on Alexandra Land in the remote Franz Josef Land archipelago of the Arctic Ocean.
-
E.
Yukhnov
Yukhnov is a small historic town in western Russia known for its location on the Ugra River and its role in regional trade and World War II history.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Nikolsk Triple: [Penza Oblast, hasCity, Nikolsk]
Generated description
Nikolsk is a small Russian town located in Penza Oblast, known for its traditional glassmaking industry and historical provincial character.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nikolsk Target entity description: Nikolsk is a small Russian town located in Penza Oblast, known for its traditional glassmaking industry and historical provincial character.
-
A.
Nikolskoye
Nikolskoye is the main and only permanent settlement on Russia’s remote Commander Islands in the Bering Sea.
-
B.
Nikolskoye
Nikolskoye is a town in northwestern Russia known as part of the Saint Petersburg metropolitan area in Leningrad Oblast.
-
C.
Nikiforovo
Nikiforovo is a village located in the mountainous Mavrovo region of North Macedonia, known for its proximity to Mavrovo National Park and Lake Mavrovo.
-
D.
Nagurskoye
Nagurskoye is a small Russian military and research settlement located on Alexandra Land in the remote Franz Josef Land archipelago of the Arctic Ocean.
-
E.
Yukhnov
Yukhnov is a small historic town in western Russia known for its location on the Ugra River and its role in regional trade and World War II history.
- F. None of above. chosen
Provenance (5 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_69e245f7b0e481909c473ff4e6a54e2c |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18e88909881908c695cd7d39d380c |
completed | April 29, 2026, 4:52 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0c23f7dccc8190aaba967e73cc6892 |
completed | May 19, 2026, 8:48 a.m. |
| NEDg | Description generation | batch_6a0c28ed782c8190a60cf2212a1e7861 |
completed | May 19, 2026, 9:10 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0c29bca4c08190a29d4204c75b333f |
completed | May 19, 2026, 9:13 a.m. |
Created at: April 17, 2026, 4 p.m.