Triple
T18466318
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University of North Alabama |
E451172
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object | UNA |
—
|
NE NERFINISHED |
How this triple was built (2 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: UNA | Statement: [University of North Alabama, abbreviation, UNA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: UNA Context triple: [University of North Alabama, abbreviation, UNA]
-
A.
UNA
UNA is the stock ticker symbol for Unilever, a major multinational consumer goods company known for its wide range of food, personal care, and household products.
-
B.
UNA
chosen
UNA is a public university located in Florence, Alabama, known for its regional academic programs and historic campus.
-
C.
UNA
UNA is the commonly used acronym for the National University of Asunción, a major public higher education institution in Paraguay.
-
D.
UNA
UNA is the commonly used acronym for the National University of Costa Rica, a major public higher education and research institution in the country.
-
E.
UNI
UNI was a 1960s–1970s American record label and imprint of MCA Records known for releasing rock, pop, and soul music.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8d38465a0819099b9b42d2a662ac1 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e52a83a27c8190aafb82f615c2dd72 |
completed | April 19, 2026, 7:18 p.m. |
Created at: April 10, 2026, 11:34 a.m.