Triple
T16234601
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Capital Airlines |
E394073
|
entity |
| Predicate | callsign |
P1565
|
FINISHED |
| Object | CAPITAL JET |
E1096108
|
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: CAPITAL JET | Statement: [Capital Airlines, callsign, CAPITAL JET]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CAPITAL JET Context triple: [Capital Airlines, callsign, CAPITAL JET]
-
A.
CAPITAL JET
chosen
CAPITAL JET is the airline callsign used by Beijing Capital Airlines for its flight operations.
-
B.
Cargojet
Cargojet is a Canadian cargo airline specializing in time-sensitive overnight air freight services across North America and select international routes.
-
C.
ANA Business Jet
ANA Business Jet is a specialized aviation company offering premium charter and business jet services under Japan’s ANA Group.
-
D.
The Jet
The Jet was the nickname of Joe Perry, a Hall of Fame NFL fullback renowned for his speed and success with the San Francisco 49ers in the 1950s.
-
E.
Avion
Avion is a commune in the Pas-de-Calais department in northern France.
- 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_69d87f204df88190a8f88923decf9835 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e24559af48819092e4b466778b07e2 |
completed | April 17, 2026, 2:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a000ed71f488190bcdc2dcc74e5c5d3 |
completed | May 10, 2026, 4:51 a.m. |
Created at: April 10, 2026, 5:04 a.m.