Triple
T5971482
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Russia and Mongolia |
E132883
|
entity |
| Predicate | borderMongolianAimags |
P67781
|
FINISHED |
| Object |
Uvs
Uvs is a province (aimag) in western Mongolia known for its vast steppe landscapes and proximity to the Russian border.
|
E559930
|
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: Uvs | Statement: [Russia and Mongolia, borderMongolianAimags, Uvs]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Uvs Context triple: [Russia and Mongolia, borderMongolianAimags, Uvs]
-
A.
Umag
Umag is a coastal town in northwestern Croatia known for its tourism, historic old town, and annual ATP tennis tournament.
-
B.
UA
UA is the two-letter ISO 3166-1 alpha-2 country code assigned to Ukraine for international standardization and identification purposes.
-
C.
UA
UA is a major public research university located in Tucson, Arizona, known for its strong programs in astronomy, space sciences, and environmental studies.
-
D.
UA
UA is the commonly used abbreviation for the University of Angers, a French public university located in Angers.
-
E.
UA
UA is a common abbreviation for the University of Arkansas, a public research university known for its flagship campus in Fayetteville.
- 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: Uvs Triple: [Russia and Mongolia, borderMongolianAimags, Uvs]
Generated description
Uvs is a province (aimag) in western Mongolia known for its vast steppe landscapes and proximity to the Russian border.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Uvs Target entity description: Uvs is a province (aimag) in western Mongolia known for its vast steppe landscapes and proximity to the Russian border.
-
A.
Umag
Umag is a coastal town in northwestern Croatia known for its tourism, historic old town, and annual ATP tennis tournament.
-
B.
UA
UA is the two-letter ISO 3166-1 alpha-2 country code assigned to Ukraine for international standardization and identification purposes.
-
C.
UA
UA is a major public research university located in Tucson, Arizona, known for its strong programs in astronomy, space sciences, and environmental studies.
-
D.
UA
UA is a major public research university located in Tuscaloosa, Alabama, known for its strong academic programs and prominent Crimson Tide athletics.
-
E.
UA
UA is the commonly used abbreviation for the University of Angers, a French public university located in Angers.
- 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_69c0086deab081908550159ca23eec9b |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c0560bae148190ad4755defaaf471b |
completed | March 22, 2026, 8:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0e40a67bc8190a57884f7c6aa1b9d |
completed | March 23, 2026, 6:56 a.m. |
| NEDg | Description generation | batch_69c0f88f4e048190810351c4aebf363c |
completed | March 23, 2026, 8:23 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c0f982c95c819081b2cf2c429c21bc |
completed | March 23, 2026, 8:27 a.m. |
Created at: March 22, 2026, 4:03 p.m.