Triple
T6637017
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Milan Bergamo Airport |
E150482
|
entity |
| Predicate | ICAO code |
P419
|
FINISHED |
| Object | LIME |
E150483
|
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: LIME | Statement: [Milan Bergamo Airport, ICAO code, LIME]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: LIME Context triple: [Milan Bergamo Airport, ICAO code, LIME]
-
A.
LIME
chosen
LIME is the ICAO airport code for Milan Bergamo Airport, a major international airport serving the Milan region in northern Italy.
-
B.
LIM
LIM is the IATA airport code for Jorge Chávez International Airport, the main international gateway serving Lima, Peru.
-
C.
LIMC
LIMC is the ICAO airport code for Milan Malpensa Airport, a major international airport serving the Milan metropolitan area in Italy.
-
D.
LIMF
LIMF is the ICAO airport code for Turin Airport, an international airport serving the city of Turin in northern Italy.
-
E.
Luma
Luma is a small, star-shaped celestial creature from the Super Mario series, known for its cute appearance and connection to Rosalina and the cosmos.
- 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_69c687f0ceb08190bf40807bfc605fa5 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6afcf439c8190b9334b34774da821 |
completed | March 27, 2026, 4:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6cbf71874819080cc89b6740b1567 |
completed | March 27, 2026, 6:27 p.m. |
Created at: March 27, 2026, 1:59 p.m.