Triple
T7949293
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Milan Malpensa Airport |
E184573
|
entity |
| Predicate | serves |
P98
|
FINISHED |
| Object | Milan metropolitan area |
E282022
|
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: Milan metropolitan area | Statement: [Milan Malpensa Airport, serves, Milan metropolitan area]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Milan metropolitan area Context triple: [Milan Malpensa Airport, serves, Milan metropolitan area]
-
A.
Metropolitan City of Milan
chosen
The Metropolitan City of Milan is an Italian administrative region centered on the city of Milan, encompassing its surrounding municipalities and serving as a major hub for finance, fashion, industry, and transportation.
-
B.
Rome metropolitan area
The Rome metropolitan area is a regional urban and economic center in northwestern Georgia, anchored by the city of Rome and its surrounding communities.
-
C.
Milan
Milan is a major Italian metropolis renowned as a global center for fashion, design, finance, and culture.
-
D.
Milan
Milan is a municipality located in Colombia’s Caquetá Department, within the Amazonian region of the country.
-
E.
Milan
Milan is a masculine given name of Slavic origin, commonly used in Central and Eastern Europe.
- 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_69ca8292cba881908a64427b938dac47 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3b2d09a4819097aa49e29a5426ec |
completed | March 31, 2026, 3:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ccbdf7679881909a14c4786c8e3e76 |
completed | April 1, 2026, 6:40 a.m. |
Created at: March 30, 2026, 5:10 p.m.