Triple
T3592131
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nenets Autonomous Okrug |
E76048
|
entity |
| Predicate | ISOCode |
P208
|
FINISHED |
| Object |
RU-NEN
RU-NEN is the ISO 3166-2 code assigned to the Nenets Autonomous Okrug, a federal subject in northwestern Russia known for its Arctic tundra and indigenous Nenets population.
|
E371786
|
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: RU-NEN | Statement: [Nenets Autonomous Okrug, ISOCode, RU-NEN]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: RU-NEN Context triple: [Nenets Autonomous Okrug, ISOCode, RU-NEN]
-
A.
RU-DA
RU-DA is the ISO 3166-2 regional code assigned to the Republic of Dagestan within the Russian Federation.
-
B.
RU-KOS
RU-KOS is the ISO 3166-2 subdivision code assigned to Kostroma Oblast, a federal subject in central Russia.
-
C.
RNO
RNO is the three-letter IATA airport code for Reno–Tahoe International Airport, the primary commercial airport serving Reno, Nevada and the surrounding Lake Tahoe region.
-
D.
RUVNN
RUVNN is the international port code assigned to the seaport of Vanino in Russia.
-
E.
RuSHA
RuSHA was a Nazi SS office responsible for implementing racial policies, including racial selection, resettlement, and the persecution and displacement of populations in occupied territories.
- 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: RU-NEN Triple: [Nenets Autonomous Okrug, ISOCode, RU-NEN]
Generated description
RU-NEN is the ISO 3166-2 code assigned to the Nenets Autonomous Okrug, a federal subject in northwestern Russia known for its Arctic tundra and indigenous Nenets population.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: RU-NEN Target entity description: RU-NEN is the ISO 3166-2 code assigned to the Nenets Autonomous Okrug, a federal subject in northwestern Russia known for its Arctic tundra and indigenous Nenets population.
-
A.
RU-DA
RU-DA is the ISO 3166-2 regional code assigned to the Republic of Dagestan within the Russian Federation.
-
B.
RU-KOS
RU-KOS is the ISO 3166-2 subdivision code assigned to Kostroma Oblast, a federal subject in central Russia.
-
C.
RNO
RNO is the three-letter IATA airport code for Reno–Tahoe International Airport, the primary commercial airport serving Reno, Nevada and the surrounding Lake Tahoe region.
-
D.
RUVNN
RUVNN is the international port code assigned to the seaport of Vanino in Russia.
-
E.
RuSHA
RuSHA was a Nazi SS office responsible for implementing racial policies, including racial selection, resettlement, and the persecution and displacement of populations in occupied territories.
- 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_69ad85d8042081908af94a04c410dec0 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc15a546481909c72dac80d65e1fb |
completed | March 8, 2026, 6:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4030bc5f081908d56edc4ff550d77 |
completed | March 13, 2026, 12:28 p.m. |
| NEDg | Description generation | batch_69b403c9f6788190be21ee4c849fba60 |
completed | March 13, 2026, 12:32 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b40872099c81909bc3531bea77f875 |
completed | March 13, 2026, 12:52 p.m. |
Created at: March 8, 2026, 3:22 p.m.