Triple
T764907
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nice Côte d’Azur Airport |
E16153
|
entity |
| Predicate | serves |
P98
|
FINISHED |
| Object | Nice |
E2387
|
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: Nice | Statement: [Nice Côte d’Azur Airport, serves, Nice]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nice Context triple: [Nice Côte d’Azur Airport, serves, Nice]
-
A.
Nice
chosen
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.
Nice Carnival
Nice Carnival is one of the world’s major and oldest carnival festivals, held annually in the French Riviera city of Nice and known for its elaborate parades, floats, and flower battles.
- 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_69a493684ee48190bd43b7c78da4aec8 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a69dfeb08190b54a476cfa66e6d6 |
completed | March 1, 2026, 8:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a76d78649c8190969a3c0c2b5a8e4d |
completed | March 3, 2026, 11:23 p.m. |
Created at: March 1, 2026, 7:37 p.m.