Triple
T5208375
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MUC |
E117567
|
entity |
| Predicate | operator |
P179
|
FINISHED |
| Object | Flughafen München GmbH |
E117566
|
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: Flughafen München GmbH | Statement: [MUC, operator, Flughafen München GmbH]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Flughafen München GmbH Context triple: [MUC, operator, Flughafen München GmbH]
-
A.
Berliner Flughafen-Gesellschaft
Berliner Flughafen-Gesellschaft was the municipal company responsible for operating Berlin’s airports, notably during the Cold War era.
-
B.
Flughafen Berlin Brandenburg GmbH
Flughafen Berlin Brandenburg GmbH is the state-owned company responsible for owning, managing, and developing Berlin’s airport infrastructure, including Berlin Brandenburg Airport.
-
C.
Munich Airport
chosen
Munich Airport is a major international aviation hub in Bavaria, Germany, serving as one of the country’s busiest airports and a key base for Lufthansa.
-
D.
Flughafen Wien AG
Flughafen Wien AG is an Austrian publicly listed company that operates and manages Vienna International Airport and related airport services.
-
E.
Nuremberg Airport
Nuremberg Airport is an international airport in northern Bavaria, Germany, serving the city of Nuremberg and the surrounding Franconia region with passenger and cargo flights.
- 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_69bd4463dd3c81909966123f20b79d57 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7a6d70d081908c74e86b3bca9ba2 |
completed | March 20, 2026, 4:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bef7ffab8c81908e17e085727304b6 |
completed | March 21, 2026, 7:56 p.m. |
Created at: March 20, 2026, 1:47 p.m.