Triple
T14787879
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sitapur district |
E347574
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object |
Laharpur
Laharpur is a town and municipal body in the Sitapur district of Uttar Pradesh, India.
|
E1119823
|
NE FINISHED |
How this triple was built (4 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: Laharpur | Statement: [Sitapur district, hasMunicipality, Laharpur]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Laharpur Context triple: [Sitapur district, hasMunicipality, Laharpur]
-
A.
Kohalpur
Kohalpur is a growing commercial and transportation hub town in southwestern Nepal, known for its strategic location on the East–West Highway.
-
B.
Labhpur
Labhpur is a town in the Birbhum district of West Bengal, India, known for its cultural heritage and association with renowned Bengali writer Tarashankar Bandyopadhyay.
-
C.
Brahmapuri
Brahmapuri is a town in Maharashtra, India, known as one of the important urban centers within Chandrapur district.
-
D.
Zaidpur
Zaidpur is a town in the Barabanki district of Uttar Pradesh, India, known for its local markets and traditional crafts.
-
E.
Taranagar
Taranagar is a town in the Churu district of Rajasthan, India, known for its regional trade, educational institutions, and cultural heritage.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Laharpur Triple: [Sitapur district, hasMunicipality, Laharpur]
Generated description
Laharpur is a town and municipal body in the Sitapur district of Uttar Pradesh, India.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Laharpur Target entity description: Laharpur is a town and municipal body in the Sitapur district of Uttar Pradesh, India.
-
A.
Kohalpur
Kohalpur is a growing commercial and transportation hub town in southwestern Nepal, known for its strategic location on the East–West Highway.
-
B.
Labhpur
Labhpur is a town in the Birbhum district of West Bengal, India, known for its cultural heritage and association with renowned Bengali writer Tarashankar Bandyopadhyay.
-
C.
Brahmapuri
Brahmapuri is a town in Maharashtra, India, known as one of the important urban centers within Chandrapur district.
-
D.
Zaidpur
Zaidpur is a town in the Barabanki district of Uttar Pradesh, India, known for its local markets and traditional crafts.
-
E.
Taranagar
Taranagar is a town in the Churu district of Rajasthan, India, known for its regional trade, educational institutions, and cultural heritage.
- F. None of above. chosen
Provenance (5 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_69d822e9b9e08190bedcc31a163fda82 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69decaa083e481908336d58d026eec32 |
completed | April 14, 2026, 11:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe24b9e8a08190bc736ac207b77324 |
completed | May 8, 2026, 6 p.m. |
| NEDg | Description generation | batch_69fe266a05308190b9f6adba3e635e2f |
completed | May 8, 2026, 6:07 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fe26f8fb7881909892c381b16fc80a |
completed | May 8, 2026, 6:10 p.m. |
Created at: April 10, 2026, 1:31 a.m.