Triple
T2963793
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Breeze Airways |
E80111
|
entity |
| Predicate | cabinClasses |
P3037
|
FINISHED |
| Object |
Nice
Nice is a cabin class offered by Breeze Airways that provides a standard, budget-friendly economy experience for passengers.
|
E314616
|
NE FINISHED |
How this triple was built (4 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: Nice | Statement: [Breeze Airways, cabinClasses, Nice]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nice Context triple: [Breeze Airways, cabinClasses, Nice]
-
A.
Nice
Nice is a prominent Mediterranean coastal city on the French Riviera, known for its mild climate, beaches, and vibrant cultural life.
-
B.
Nice Agreement
The Nice Agreement is an international treaty that establishes a standardized classification system of goods and services used for the registration of trademarks.
-
C.
FRIENDLY
FRIENDLY is the airline callsign used by Southern Airways Express, a U.S.-based commuter and regional airline.
-
D.
Nice Classification
Nice Classification is an international system that categorizes goods and services into standardized classes for the registration of trademarks.
-
E.
Be Nice
"Be Nice" is a song by the American hip hop group Black Eyed Peas featuring Snoop Dogg, known for its upbeat message promoting kindness and positivity.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Nice Triple: [Breeze Airways, cabinClasses, Nice]
Generated description
Nice is a cabin class offered by Breeze Airways that provides a standard, budget-friendly economy experience for passengers.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nice Target entity description: Nice is a cabin class offered by Breeze Airways that provides a standard, budget-friendly economy experience for passengers.
-
A.
Nice
Nice is a prominent Mediterranean coastal city on the French Riviera, known for its mild climate, beaches, and vibrant cultural life.
-
B.
Nice Agreement
The Nice Agreement is an international treaty that establishes a standardized classification system of goods and services used for the registration of trademarks.
-
C.
FRIENDLY
FRIENDLY is the airline callsign used by Southern Airways Express, a U.S.-based commuter and regional airline.
-
D.
Nice Classification
Nice Classification is an international system that categorizes goods and services into standardized classes for the registration of trademarks.
-
E.
Be Nice
"Be Nice" is a song by the American hip hop group Black Eyed Peas featuring Snoop Dogg, known for its upbeat message promoting kindness and positivity.
- F. None of above. chosen
Provenance (5 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_69ad8b1341848190bd19dbf46892887d |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9957602c819089b673966fd619e0 |
completed | March 8, 2026, 3:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b0fc98d94481908282d21394dc24a7 |
completed | March 11, 2026, 5:24 a.m. |
| NEDg | Description generation | batch_69b0fd07b82881908d52ab2db2f2e54c |
completed | March 11, 2026, 5:26 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b0fdba0fd88190a2e760f1770e846c |
completed | March 11, 2026, 5:29 a.m. |
Created at: March 8, 2026, 2:58 p.m.