Triple
T16197696
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UTair |
E393109
|
entity |
| Predicate | ICAOcode |
P419
|
FINISHED |
| Object | UTA |
E345304
|
NE FINISHED |
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: UTA | Statement: [UTair, ICAOcode, UTA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: UTA Context triple: [UTair, ICAOcode, UTA]
-
A.
UTA
UTA is the three-letter IATA airport code assigned to Mutare Airport in Zimbabwe.
-
B.
UTA
chosen
UTA is the ICAO airline designator used to identify UTair Aviation in international aviation operations.
-
C.
UTA
UTA is a large public research university located in Arlington, Texas, known for its diverse student body and strong engineering, business, and nursing programs.
-
D.
UTA
UTA is the public-facing brand name of the Utah Transit Authority, which operates bus, light rail, commuter rail, and other transit services across the Wasatch Front in Utah.
-
E.
Utah State University
Utah State University is a public land-grant research university in Logan, Utah, known for its strong programs in agriculture, engineering, and natural resources.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d87f1e49ac8190a311b54d32990576 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e222dc6b1c8190a3d8a6451ed8b95a |
completed | April 17, 2026, 12:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffff0f352081908324783743e47029 |
completed | May 10, 2026, 3:44 a.m. |
Created at: April 10, 2026, 5:02 a.m.