Dibiyapur
E1021419
Dibiyapur is a small industrial town in the Auraiya district of Uttar Pradesh, India, known for its power and gas-based industries.
All labels observed (3)
| Label | Occurrences |
|---|---|
| Dibiyapur canonical | 2 |
| Dibiyapur town | 1 |
| Dibiyapur township | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T13071136 — 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: Dibiyapur Context triple: [Auraiya district, hasTown, Dibiyapur]
-
A.
Babatpur
Babatpur is a locality near Varanasi in the Indian state of Uttar Pradesh, known primarily for hosting the city’s main airport.
-
B.
Jangipur
Jangipur is a town in the Murshidabad district of the Indian state of West Bengal, known for its administrative significance and proximity to the Ganges River.
-
C.
Mahidpur
Mahidpur is a historic town in the Indian state of Madhya Pradesh, known for its location in the Malwa region and its role in the Anglo-Maratha conflicts.
-
D.
Baruipur
Baruipur is a suburban town and municipality in West Bengal, India, known as an important residential and commercial hub near Kolkata.
-
E.
Bhatkuli
Bhatkuli is a small town in the Amravati district of Maharashtra, India, known primarily as a local administrative and market center for surrounding rural areas.
- 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: Dibiyapur Target entity description: Dibiyapur is a small industrial town in the Auraiya district of Uttar Pradesh, India, known for its power and gas-based industries.
-
A.
Babatpur
Babatpur is a locality near Varanasi in the Indian state of Uttar Pradesh, known primarily for hosting the city’s main airport.
-
B.
Jangipur
Jangipur is a town in the Murshidabad district of the Indian state of West Bengal, known for its administrative significance and proximity to the Ganges River.
-
C.
Mahidpur
Mahidpur is a historic town in the Indian state of Madhya Pradesh, known for its location in the Malwa region and its role in the Anglo-Maratha conflicts.
-
D.
Baruipur
Baruipur is a suburban town and municipality in West Bengal, India, known as an important residential and commercial hub near Kolkata.
-
E.
Bhatkuli
Bhatkuli is a small town in the Amravati district of Maharashtra, India, known primarily as a local administrative and market center for surrounding rural areas.
- F. None of above. chosen
Statements (30)
| Predicate | Object |
|---|---|
| instanceOf |
human settlement
ⓘ
town ⓘ |
| climate | humid subtropical climate ⓘ |
| country | India ⓘ |
| economicActivity |
industrial production
ⓘ
natural gas-based industry ⓘ power generation ⓘ |
| governingBody | local municipal authorities ⓘ |
| hasDistrict | Auraiya district ⓘ |
| hasIndustrialArea |
gas-based power plants
ⓘ
power generation facilities ⓘ |
| hasNearbyCity |
Auraiya
ⓘ
Kanpur ⓘ |
| hasState | Uttar Pradesh ⓘ |
| hasTransport |
railway connectivity
ⓘ
road connectivity ⓘ |
| knownFor |
gas-based industry
ⓘ
power industry ⓘ |
| language | Hindi ⓘ |
| locatedIn |
Auraiya district
ⓘ
Indo-Gangetic plain ⓘ
linked to:
Indo-Gangetic Plain
Kanpur division ⓘ Northern India ⓘ
linked to:
northern India
Uttar Pradesh ⓘ |
| officialLanguage | Hindi ⓘ |
| partOf | Auraiya district urban and industrial belt ⓘ |
| regionalLanguage |
Awadhi
ⓘ
Braj Bhasha ⓘ |
| timeZone | Indian Standard Time ⓘ |
| UTCOffset | +5:30 ⓘ |
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: Dibiyapur Description of subject: Dibiyapur is a small industrial town in the Auraiya district of Uttar Pradesh, India, known for its power and gas-based industries.
Referenced by (4)
Full triples — surface form annotated when it differs from this entity's canonical label.
linked to: Dibiyapur
linked to: Dibiyapur