Triple
T1740578
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FVEY |
E38222
|
entity |
| Predicate | hasAbbreviation |
P43
|
FINISHED |
| Object | FVEY |
E38222
|
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: FVEY | Statement: [FVEY, hasAbbreviation, FVEY]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: FVEY Context triple: [FVEY, hasAbbreviation, FVEY]
-
A.
FVEY
chosen
FVEY is an abbreviation for the Five Eyes, an intelligence alliance comprising Australia, Canada, New Zealand, the United Kingdom, and the United States that cooperates on signals intelligence and security matters.
-
B.
YV
YV is the IATA airline designator used to identify Mesa Airlines in flight schedules and ticketing systems.
-
C.
FÜ
FÜ is the vehicle registration code used on license plates for the city of Fürth in Bavaria, Germany.
-
D.
HVF
HVF is a data-focused startup and innovation lab created by entrepreneur Max Levchin to explore and build companies around large-scale data problems.
-
E.
VY
VY is the IATA airline designator assigned to Vueling, a Spanish low-cost carrier based in Barcelona.
- 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_69a8862b01a48190ab47209063af82d9 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aa63c5ab648190bceae2a19fa18e87 |
completed | March 6, 2026, 5:19 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad8b060d64819096ba0522ccce9145 |
completed | March 8, 2026, 2:43 p.m. |
Created at: March 4, 2026, 7:30 p.m.