MQA
E779524
MQA is the station code for the Mexico City Metro station named after Mexican engineer and environmentalist Miguel Ángel de Quevedo.
All labels observed (1)
| Label | Occurrences |
|---|---|
| MQA canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T9118725 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MQA Context triple: [Miguel Ángel de Quevedo, hasStationCode, MQA]
-
A.
MQA
MQA (Master Quality Authenticated) is a proprietary audio codec and encoding technology designed to deliver high-resolution, studio-quality sound in relatively small file sizes for streaming and playback.
-
B.
Monkey's Audio
Monkey's Audio is a lossless audio compression format and codec known for its high compression ratios and Windows-focused software tools.
-
C.
Dolby MAT
Dolby MAT (Metadata-enhanced Audio Transmission) is an audio format and transport technology developed by Dolby that carries object-based Dolby Atmos sound and metadata over HDMI for home theater and consumer devices.
-
D.
Dolby TrueHD
Dolby TrueHD is a lossless multichannel audio codec designed for high-definition home entertainment formats like Blu-ray to deliver studio-quality surround sound.
-
E.
WMA
WMA is a proprietary audio compression format developed by Microsoft as part of its Windows Media framework.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: MQA Target entity description: MQA is the station code for the Mexico City Metro station named after Mexican engineer and environmentalist Miguel Ángel de Quevedo.
-
A.
MQA
MQA (Master Quality Authenticated) is a proprietary audio codec and encoding technology designed to deliver high-resolution, studio-quality sound in relatively small file sizes for streaming and playback.
-
B.
Monkey's Audio
Monkey's Audio is a lossless audio compression format and codec known for its high compression ratios and Windows-focused software tools.
-
C.
Dolby MAT
Dolby MAT (Metadata-enhanced Audio Transmission) is an audio format and transport technology developed by Dolby that carries object-based Dolby Atmos sound and metadata over HDMI for home theater and consumer devices.
-
D.
Dolby TrueHD
Dolby TrueHD is a lossless multichannel audio codec designed for high-definition home entertainment formats like Blu-ray to deliver studio-quality surround sound.
-
E.
WMA
WMA is a proprietary audio compression format developed by Microsoft as part of its Windows Media framework.
- F. None of above. chosen
Statements (27)
| Predicate | Object |
|---|---|
| instanceOf |
metro station code
ⓘ
transportation station identifier ⓘ |
| appliesToStation | Miguel Ángel de Quevedo ⓘ |
| appliesToSystem | Mexico City Metro ⓘ |
| city | Mexico City ⓘ |
| codeForLanguage | Spanish ⓘ |
| codeLength | 3 ⓘ |
| codeType | alphabetic ⓘ |
| country | Mexico ⓘ |
| hasInitial |
A
ⓘ
M ⓘ Q ⓘ |
| namedAfter | Miguel Ángel de Quevedo ⓘ |
| namedAfterCountry | Mexico ⓘ |
| namedAfterOccupation |
engineer
ⓘ
environmentalist ⓘ |
| relatedToField |
civil engineering
ⓘ
environmentalism ⓘ |
| relatedToPerson | Miguel Ángel de Quevedo ⓘ |
| stationName | Miguel Ángel de Quevedo ⓘ |
| transportMode |
metro
ⓘ
rapid transit ⓘ |
| transportNetwork | Sistema de Transporte Colectivo Metro ⓘ |
| usedBy |
Mexico City Metro operators
ⓘ
linked to:
operations directorate of Mexico City Metro
|
| usedFor |
mapping and scheduling
ⓘ
operational identification of station ⓘ signage and information systems ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: MQA Description of subject: MQA is the station code for the Mexico City Metro station named after Mexican engineer and environmentalist Miguel Ángel de Quevedo.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.