ML-2
E632088
ML-2 is a major north–south railway corridor in Pakistan that serves as one of the country’s principal main lines parallel to the primary ML-1 route.
All labels observed (1)
| Label | Occurrences |
|---|---|
| ML-2 canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T6932681 — 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: ML-2 Context triple: [Pakistan Railways network, hasCorridor, ML-2]
-
A.
ML-1
ML-1 is Pakistan Railways’ primary north–south main line, connecting major cities and serving as the backbone of the country’s rail transport system.
-
B.
ML3
ML3 is a UK postcode district covering part of Hamilton and surrounding areas in South Lanarkshire, Scotland.
-
C.
ML10
ML10 is a postcode district within the ML (Motherwell) postcode area in central Scotland, covering Strathaven and surrounding settlements.
-
D.
MLI
MLI is the three-letter ISO 3166-1 alpha-3 country code assigned to Mali.
-
E.
MLC
MLC is the upper house of the bicameral legislature of the Indian state of Maharashtra, responsible for reviewing and passing state legislation.
- 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: ML-2 Target entity description: ML-2 is a major north–south railway corridor in Pakistan that serves as one of the country’s principal main lines parallel to the primary ML-1 route.
-
A.
ML-1
ML-1 is Pakistan Railways’ primary north–south main line, connecting major cities and serving as the backbone of the country’s rail transport system.
-
B.
ML3
ML3 is a UK postcode district covering part of Hamilton and surrounding areas in South Lanarkshire, Scotland.
-
C.
ML10
ML10 is a postcode district within the ML (Motherwell) postcode area in central Scotland, covering Strathaven and surrounding settlements.
-
D.
MLI
MLI is the three-letter ISO 3166-1 alpha-3 country code assigned to Mali.
-
E.
MLC
MLC is the upper house of the bicameral legislature of the Indian state of Maharashtra, responsible for reviewing and passing state legislation.
- F. None of above. chosen
Statements (47)
| Predicate | Object |
|---|---|
| instanceOf |
railway corridor
ⓘ
railway line ⓘ |
| connects |
Attock City
NERFINISHED
ⓘ
Kotri NERFINISHED ⓘ |
| country | Pakistan ⓘ |
| electrification | not electrified ⓘ |
| endPoint | Attock City Junction NERFINISHED ⓘ |
| gauge |
1,676 mm broad gauge
ⓘ
5 ft 6 in broad gauge ⓘ |
| locatedIn |
Khyber Pakhtunkhwa, Pakistan
NERFINISHED
ⓘ
Punjab, Pakistan NERFINISHED ⓘ |
| networkRole |
main line
ⓘ
principal railway corridor ⓘ |
| operator | Pakistan Railways NERFINISHED ⓘ |
| orientation | north–south ⓘ |
| ownedBy | Government of Pakistan NERFINISHED ⓘ |
| parallelTo | ML-1 NERFINISHED ⓘ |
| partOf | Pakistan Railways main line network NERFINISHED ⓘ |
| passesThrough |
Attock City
NERFINISHED
ⓘ
Bhakkar NERFINISHED ⓘ Dadu NERFINISHED ⓘ Daud Khel NERFINISHED ⓘ Dera Allah Yar NERFINISHED ⓘ Dera Ghazi Khan NERFINISHED ⓘ Dera Murad Jamali NERFINISHED ⓘ Injra ⓘ Jacobabad NERFINISHED ⓘ Kundian NERFINISHED ⓘ Larkana NERFINISHED ⓘ Mianwali NERFINISHED ⓘ Multan NERFINISHED ⓘ Muzaffargarh NERFINISHED ⓘ Rakhni ⓘ Shikarpur NERFINISHED ⓘ Sibi NERFINISHED ⓘ |
| railwaySystem | Pakistan Railways NERFINISHED ⓘ |
| regionServed |
Balochistan
NERFINISHED
ⓘ
Khyber Pakhtunkhwa NERFINISHED ⓘ Punjab NERFINISHED ⓘ Sindh NERFINISHED ⓘ |
| servesAs | alternative route to ML-1 ⓘ |
| startPoint | Kotri Junction NERFINISHED ⓘ |
| status | operational ⓘ |
| strategicImportance | forms secondary spine parallel to ML-1 ⓘ |
| trackConfiguration | single track ⓘ |
| usedFor |
freight rail transport
ⓘ
passenger rail transport ⓘ |
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: ML-2 Description of subject: ML-2 is a major north–south railway corridor in Pakistan that serves as one of the country’s principal main lines parallel to the primary ML-1 route.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.