Triple
T2273562
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Darbhanga district |
E50716
|
entity |
| Predicate | hasTown |
P847
|
FINISHED |
| Object |
Benipur
Benipur is a town in the Darbhanga region of the Indian state of Bihar, known as a local center of trade and daily commerce.
|
E254793
|
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: Benipur | Statement: [Darbhanga district, hasTown, Benipur]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Benipur Context triple: [Darbhanga district, hasTown, Benipur]
-
A.
Benipatti
Benipatti is a town in the Madhubani district of the Indian state of Bihar, known for its rural setting and proximity to the region’s famed Mithila culture.
-
B.
Alipurduar
Alipurduar is a town in northeastern West Bengal, India, known as a gateway to the Dooars region and several nearby wildlife sanctuaries and national parks.
-
C.
Kasarani
Kasarani is a residential and commercial suburb in northeastern Nairobi, Kenya, known for hosting major sports and educational facilities.
-
D.
Ghoghardiha
Ghoghardiha is a town located in the Madhubani district of the Indian state of Bihar.
-
E.
Verbania
Verbania is a lakeside city in northern Italy, situated on the shores of Lake Maggiore near the Swiss border.
- 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: Benipur Triple: [Darbhanga district, hasTown, Benipur]
Generated description
Benipur is a town in the Darbhanga region of the Indian state of Bihar, known as a local center of trade and daily commerce.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Benipur Target entity description: Benipur is a town in the Darbhanga region of the Indian state of Bihar, known as a local center of trade and daily commerce.
-
A.
Benipatti
Benipatti is a town in the Madhubani district of the Indian state of Bihar, known for its rural setting and proximity to the region’s famed Mithila culture.
-
B.
Alipurduar
Alipurduar is a town in northeastern West Bengal, India, known as a gateway to the Dooars region and several nearby wildlife sanctuaries and national parks.
-
C.
Kasarani
Kasarani is a residential and commercial suburb in northeastern Nairobi, Kenya, known for hosting major sports and educational facilities.
-
D.
Ghoghardiha
Ghoghardiha is a town located in the Madhubani district of the Indian state of Bihar.
-
E.
Verbania
Verbania is a lakeside city in northern Italy, situated on the shores of Lake Maggiore near the Swiss border.
- 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_69a88b05910c8190a9a2b1ff230c85f9 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc1ea6cc88190982527774223127f |
completed | March 7, 2026, 6:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae894a20e0819097f08959f7a062ef |
completed | March 9, 2026, 8:48 a.m. |
| NEDg | Description generation | batch_69ae89e2efd48190a2f0a4702dcbc081 |
completed | March 9, 2026, 8:50 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae8a7726dc8190a18f7f1e1609253a |
completed | March 9, 2026, 8:53 a.m. |
Created at: March 4, 2026, 7:48 p.m.