Triple
T12255574
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Diveyevo Monastery |
E292091
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object |
Diveyevo
Diveyevo is a Russian village in Nizhny Novgorod Oblast best known as a major Orthodox pilgrimage center due to the presence of the Seraphim-Diveyevo Monastery.
|
E972635
|
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: Diveyevo | Statement: [Diveyevo Monastery, locatedIn, Diveyevo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Diveyevo Context triple: [Diveyevo Monastery, locatedIn, Diveyevo]
-
A.
Yazhelbitsy
Yazhelbitsy is a rural locality in Russia known for its proximity to Mount Uzhin.
-
B.
Vidyaevo
Vidyaevo is a closed naval settlement in Murmansk Oblast, Russia, known primarily as a major submarine base of the Russian Northern Fleet.
-
C.
Khopyor
Khopyor is a major river in southwestern Russia that flows through the Central Russian Upland before joining the Don River.
-
D.
Devnya
Devnya is an industrial town in northeastern Bulgaria known for its large chemical and cement plants and its location near the Black Sea port city of Varna.
-
E.
Vishkanya
Vishkanya is a 1991 Indian Hindi-language horror film known for its supernatural revenge plot and early appearance of actress Riya Sen.
- 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: Diveyevo Triple: [Diveyevo Monastery, locatedIn, Diveyevo]
Generated description
Diveyevo is a Russian village in Nizhny Novgorod Oblast best known as a major Orthodox pilgrimage center due to the presence of the Seraphim-Diveyevo Monastery.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Diveyevo Target entity description: Diveyevo is a Russian village in Nizhny Novgorod Oblast best known as a major Orthodox pilgrimage center due to the presence of the Seraphim-Diveyevo Monastery.
-
A.
Yazhelbitsy
Yazhelbitsy is a rural locality in Russia known for its proximity to Mount Uzhin.
-
B.
Vidyaevo
Vidyaevo is a closed naval settlement in Murmansk Oblast, Russia, known primarily as a major submarine base of the Russian Northern Fleet.
-
C.
Khopyor
Khopyor is a major river in southwestern Russia that flows through the Central Russian Upland before joining the Don River.
-
D.
Devnya
Devnya is an industrial town in northeastern Bulgaria known for its large chemical and cement plants and its location near the Black Sea port city of Varna.
-
E.
Vishkanya
Vishkanya is a 1991 Indian Hindi-language horror film known for its supernatural revenge plot and early appearance of actress Riya Sen.
- 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_69d6ab67950c8190be08450a06228c4b |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d91cc9dd5081908880061d52351850 |
completed | April 10, 2026, 3:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f60abdc5988190a19104385f54fb06 |
completed | May 2, 2026, 2:31 p.m. |
| NEDg | Description generation | batch_69f60d8456d881908b5647b77fc53780 |
completed | May 2, 2026, 2:43 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f60e2c52b0819094c8e67286235400 |
completed | May 2, 2026, 2:46 p.m. |
Created at: April 8, 2026, 9:52 p.m.