Triple
T15410389
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ulchsky District |
E368573
|
entity |
| Predicate | administrativeCenter |
P1474
|
FINISHED |
| Object |
Bogorodskoye
Bogorodskoye is a rural locality in Russia that serves as the main administrative hub of Ulchsky District in Khabarovsk Krai.
|
E1158921
|
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: Bogorodskoye | Statement: [Ulchsky District, administrativeCenter, Bogorodskoye]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bogorodskoye Context triple: [Ulchsky District, administrativeCenter, Bogorodskoye]
-
A.
Bogorodskoye
Bogorodskoye is a rural locality in Russia that serves as one of the settlements within Nikolaevsky District.
-
B.
Bogorodsk
Bogorodsk is a historic Russian town that developed as a regional center of trade and crafts within the former Moscow Governorate.
-
C.
Bogoroditsk
Bogoroditsk is a small historic town in western Russia known for its 18th-century palace-and-park ensemble and its role as a local industrial and cultural center.
-
D.
Voskresensk
Voskresensk is a town in Moscow Oblast, Russia, known for its industrial base and strong ice hockey tradition.
-
E.
Belozersk
Belozersk is a historic town in northwestern Russia known for its medieval heritage and location near Lake Beloye.
- 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: Bogorodskoye Triple: [Ulchsky District, administrativeCenter, Bogorodskoye]
Generated description
Bogorodskoye is a rural locality in Russia that serves as the main administrative hub of Ulchsky District in Khabarovsk Krai.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bogorodskoye Target entity description: Bogorodskoye is a rural locality in Russia that serves as the main administrative hub of Ulchsky District in Khabarovsk Krai.
-
A.
Bogorodskoye
Bogorodskoye is a rural locality in Russia that serves as one of the settlements within Nikolaevsky District.
-
B.
Bogorodsk
Bogorodsk is a historic Russian town that developed as a regional center of trade and crafts within the former Moscow Governorate.
-
C.
Bogoroditsk
Bogoroditsk is a small historic town in western Russia known for its 18th-century palace-and-park ensemble and its role as a local industrial and cultural center.
-
D.
Voskresensk
Voskresensk is a town in Moscow Oblast, Russia, known for its industrial base and strong ice hockey tradition.
-
E.
Belozersk
Belozersk is a historic town in northwestern Russia known for its medieval heritage and location near Lake Beloye.
- 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_69d85a16c68c819099c1b547fbc87b32 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03ea4f13c819085d26fd32b5dca6f |
completed | April 16, 2026, 1:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff2cf0e90c8190a339e6fca53a02d8 |
completed | May 9, 2026, 12:47 p.m. |
| NEDg | Description generation | batch_69ff2e1fb27c81908de0d755bf30c833 |
completed | May 9, 2026, 12:52 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff2f3ab6988190b4cefe2f55c4101c |
completed | May 9, 2026, 12:57 p.m. |
Created at: April 10, 2026, 3:20 a.m.