Triple
T10311092
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karakalpakstan |
E241889
|
entity |
| Predicate | hasISO3166-2Code |
P208
|
FINISHED |
| Object |
UZ-QR
UZ-QR is the ISO 3166-2 subdivision code assigned to the autonomous Republic of Karakalpakstan within Uzbekistan.
|
E855698
|
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: UZ-QR | Statement: [Karakalpakstan, hasISO3166-2Code, UZ-QR]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: UZ-QR Context triple: [Karakalpakstan, hasISO3166-2Code, UZ-QR]
-
A.
UZ
UZ is the two-letter ISO 3166-1 alpha-2 country code assigned to Uzbekistan.
-
B.
UZS
UZS is the official currency code for the Uzbekistani soʻm, the national currency of Uzbekistan.
-
C.
UzK
UzK is the commonly used abbreviation for the University of Cologne, one of Germany’s largest and oldest universities.
-
D.
Uzh
Uzh is a river in Eastern Europe that flows through western Ukraine and Slovakia, serving as an important waterway for the Zakarpattia region.
-
E.
GZQ
GZQ is the station code used to identify Guangzhou Railway Station, a major rail transport hub in Guangzhou, China.
- 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: UZ-QR Triple: [Karakalpakstan, hasISO3166-2Code, UZ-QR]
Generated description
UZ-QR is the ISO 3166-2 subdivision code assigned to the autonomous Republic of Karakalpakstan within Uzbekistan.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: UZ-QR Target entity description: UZ-QR is the ISO 3166-2 subdivision code assigned to the autonomous Republic of Karakalpakstan within Uzbekistan.
-
A.
UZ
UZ is the two-letter ISO 3166-1 alpha-2 country code assigned to Uzbekistan.
-
B.
UZS
UZS is the official currency code for the Uzbekistani soʻm, the national currency of Uzbekistan.
-
C.
UzK
UzK is the commonly used abbreviation for the University of Cologne, one of Germany’s largest and oldest universities.
-
D.
Uzh
Uzh is a river in Eastern Europe that flows through western Ukraine and Slovakia, serving as an important waterway for the Zakarpattia region.
-
E.
GZQ
GZQ is the station code used to identify Guangzhou Railway Station, a major rail transport hub in Guangzhou, China.
- 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_69d381ac38808190a8ca7457c85b625b |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d32ac6c08190b23eb042b3ec284a |
completed | April 7, 2026, 9:49 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d71d78ece88190885768c979b038df |
completed | April 9, 2026, 3:31 a.m. |
| NEDg | Description generation | batch_69d73186831481909555e2205d8783a7 |
completed | April 9, 2026, 4:56 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d732bfc76c819089287477b54a7b77 |
completed | April 9, 2026, 5:01 a.m. |
Created at: April 6, 2026, 11:47 a.m.