Triple
T2332039
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United Airlines Flight 93 |
E44223
|
entity |
| Predicate | operatorIATACode |
P418
|
FINISHED |
| Object | UA |
E47401
|
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: UA | Statement: [United Airlines Flight 93, operatorIATACode, UA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: UA Context triple: [United Airlines Flight 93, operatorIATACode, UA]
-
A.
UA
UA is a major public research university located in Tucson, Arizona, known for its strong programs in astronomy, space sciences, and environmental studies.
-
B.
UA
chosen
UA is the two-letter IATA airline designator used worldwide to identify United Airlines on tickets, schedules, and flight information.
-
C.
UA
UA is a major public research university located in Tuscaloosa, Alabama, known for its strong academic programs and prominent Crimson Tide athletics.
-
D.
UA
UA is the two-letter ISO 3166-1 alpha-2 country code assigned to Ukraine for international standardization and identification purposes.
-
E.
UA
UA is the commonly used abbreviation for the University of Angers, a French public university located in Angers.
- 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_69a889132b488190bbb43ad4780ddd92 |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abc66bd0f08190aad5f640cfa1c372 |
completed | March 7, 2026, 6:32 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae89773c88819087a294d7c0f90f73 |
completed | March 9, 2026, 8:48 a.m. |
Created at: March 4, 2026, 7:51 p.m.