Triple
T7913798
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chandrapur district |
E183764
|
entity |
| Predicate | hasNotableTown |
P14082
|
FINISHED |
| Object |
Brahmapuri
Brahmapuri is a town in Maharashtra, India, known as one of the important urban centers within Chandrapur district.
|
E717687
|
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: Brahmapuri | Statement: [Chandrapur district, hasNotableTown, Brahmapuri]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brahmapuri Context triple: [Chandrapur district, hasNotableTown, Brahmapuri]
-
A.
Vikrampura
Vikrampura was an important historical city that served as a principal royal center of the medieval Indian Pala dynasty in eastern India.
-
B.
Karanpur
Karanpur is a town located in the Ganganagar district of the northern Indian state of Rajasthan.
-
C.
Kohalpur
Kohalpur is a growing commercial and transportation hub town in southwestern Nepal, known for its strategic location on the East–West Highway.
-
D.
Partapur
Partapur is a locality in Meerut district of Uttar Pradesh, India, known for its proximity to the Dr. Bhimrao Ambedkar Airstrip and its growing urban and institutional development.
-
E.
Babatpur
Babatpur is a locality near Varanasi in the Indian state of Uttar Pradesh, known primarily for hosting the city’s main airport.
- 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: Brahmapuri Triple: [Chandrapur district, hasNotableTown, Brahmapuri]
Generated description
Brahmapuri is a town in Maharashtra, India, known as one of the important urban centers within Chandrapur district.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Brahmapuri Target entity description: Brahmapuri is a town in Maharashtra, India, known as one of the important urban centers within Chandrapur district.
-
A.
Vikrampura
Vikrampura was an important historical city that served as a principal royal center of the medieval Indian Pala dynasty in eastern India.
-
B.
Karanpur
Karanpur is a town located in the Ganganagar district of the northern Indian state of Rajasthan.
-
C.
Kohalpur
Kohalpur is a growing commercial and transportation hub town in southwestern Nepal, known for its strategic location on the East–West Highway.
-
D.
Partapur
Partapur is a locality in Meerut district of Uttar Pradesh, India, known for its proximity to the Dr. Bhimrao Ambedkar Airstrip and its growing urban and institutional development.
-
E.
Babatpur
Babatpur is a locality near Varanasi in the Indian state of Uttar Pradesh, known primarily for hosting the city’s main airport.
- 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_69ca828dec0c81908b8f55a4dbbb53ff |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3a748f4c8190bcd868de2fcf0b3a |
completed | March 31, 2026, 3:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ccec781ac88190b52305beaa213415 |
completed | April 1, 2026, 9:59 a.m. |
| NEDg | Description generation | batch_69ccf0982f4481908e2a59424fdf470f |
completed | April 1, 2026, 10:16 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cd051913708190a83f925cf0cbbaa1 |
completed | April 1, 2026, 11:44 a.m. |
Created at: March 30, 2026, 5:04 p.m.