Triple
T7483661
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Darrang district |
E176824
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object |
Sipajhar
Sipajhar is a town and administrative center in the Indian state of Assam, known for its role as a local hub within Darrang district.
|
E690849
|
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: Sipajhar | Statement: [Darrang district, containsSettlement, Sipajhar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sipajhar Context triple: [Darrang district, containsSettlement, Sipajhar]
-
A.
Baripada
Baripada is a prominent town and district headquarters in the Mayurbhanj district of Odisha, India, known for its cultural heritage and proximity to the Simlipal National Park.
-
B.
Sainthia
Sainthia is a town in the Birbhum district of West Bengal, India, known as a local commercial and cultural center.
-
C.
Basirhat
Basirhat is a town in the North 24 Parganas district of West Bengal, India, known as a regional administrative and commercial center near the India–Bangladesh border.
-
D.
Muktainagar
Muktainagar is a town in the Jalgaon district of Maharashtra, India, known primarily as an agricultural and trading center in the region.
-
E.
Santipur
Santipur is a historic town in West Bengal, India, renowned for its traditional handloom sarees 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: Sipajhar Triple: [Darrang district, containsSettlement, Sipajhar]
Generated description
Sipajhar is a town and administrative center in the Indian state of Assam, known for its role as a local hub within Darrang district.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sipajhar Target entity description: Sipajhar is a town and administrative center in the Indian state of Assam, known for its role as a local hub within Darrang district.
-
A.
Baripada
Baripada is a prominent town and district headquarters in the Mayurbhanj district of Odisha, India, known for its cultural heritage and proximity to the Simlipal National Park.
-
B.
Sainthia
Sainthia is a town in the Birbhum district of West Bengal, India, known as a local commercial and cultural center.
-
C.
Basirhat
Basirhat is a town in the North 24 Parganas district of West Bengal, India, known as a regional administrative and commercial center near the India–Bangladesh border.
-
D.
Muktainagar
Muktainagar is a town in the Jalgaon district of Maharashtra, India, known primarily as an agricultural and trading center in the region.
-
E.
Santipur
Santipur is a historic town in West Bengal, India, renowned for its traditional handloom sarees 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_69c69f24ac508190bb98fe927c0bd065 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f53923e4819081bf79ed962a971c |
completed | March 27, 2026, 9:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c9567fd22881909bd8f4972144be22 |
completed | March 29, 2026, 4:42 p.m. |
| NEDg | Description generation | batch_69c95717609c8190973fd6fac4e6311b |
completed | March 29, 2026, 4:45 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c9573a86808190b9b5dfce95dd74fb |
completed | March 29, 2026, 4:45 p.m. |
Created at: March 27, 2026, 3:42 p.m.