Triple
T1153286
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University of Arizona |
E23725
|
entity |
| Predicate | acronym |
P43
|
FINISHED |
| Object |
UA
UA is a major public research university located in Tucson, Arizona, known for its strong programs in astronomy, space sciences, and environmental studies.
|
E133728
|
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: UA | Statement: [University of Arizona, acronym, UA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: UA Context triple: [University of Arizona, acronym, UA]
-
A.
UA
UA is a major public research university located in Tuscaloosa, Alabama, known for its strong academic programs and prominent Crimson Tide athletics.
-
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 the two-letter IATA airline designator used worldwide to identify United Airlines on tickets, schedules, and flight information.
-
D.
UAL
UAL is the ICAO airline designator used to identify United Airlines in aviation operations and air traffic control.
-
E.
CU
CU is the two-letter ISO 3166-1 alpha-2 country code assigned to Cuba.
- 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: UA Triple: [University of Arizona, acronym, UA]
Generated description
UA is a major public research university located in Tucson, Arizona, known for its strong programs in astronomy, space sciences, and environmental studies.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: UA Target entity description: UA is a major public research university located in Tucson, Arizona, known for its strong programs in astronomy, space sciences, and environmental studies.
-
A.
UA
UA is the two-letter IATA airline designator used worldwide to identify United Airlines on tickets, schedules, and flight information.
-
B.
UA
UA is a major public research university located in Tuscaloosa, Alabama, known for its strong academic programs and prominent Crimson Tide athletics.
-
C.
UA
UA is the two-letter ISO 3166-1 alpha-2 country code assigned to Ukraine for international standardization and identification purposes.
-
D.
UAL
UAL is the ICAO airline designator used to identify United Airlines in aviation operations and air traffic control.
-
E.
CU
CU is the two-letter ISO 3166-1 alpha-2 country code assigned to Cuba.
- 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_69a493f0d32c8190ac74bad3c87f2641 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4bc8e9cb481908a528a828b21d497 |
completed | March 1, 2026, 10:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac667a61248190b71033daadef58e3 |
completed | March 7, 2026, 5:55 p.m. |
| NEDg | Description generation | batch_69ac66e3fecc81908638052a417ce4ab |
completed | March 7, 2026, 5:56 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ac67ab1ab48190b857bd473e741417 |
completed | March 7, 2026, 6 p.m. |
Created at: March 1, 2026, 7:44 p.m.