Triple
T21668125
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Old Dhaka |
E534773
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Bangshal
Bangshal is a historic, densely populated neighborhood in Old Dhaka, Bangladesh, known for its traditional markets and vibrant urban life.
|
E1494985
|
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: Bangshal | Statement: [Old Dhaka, contains, Bangshal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bangshal Context triple: [Old Dhaka, contains, Bangshal]
-
A.
Bangash
Bangash is a prominent Karlani Pashtun tribe historically settled in parts of present-day Pakistan and Afghanistan.
-
B.
Khanakul
Khanakul is a town in the Hooghly district of West Bengal, India, known for its rural setting and local agricultural economy.
-
C.
Bhangar
Bhangar is a town in the South 24 Parganas district of West Bengal, India, known for its semi-urban character and proximity to Kolkata.
-
D.
Sandeshkhali
Sandeshkhali is a rural town and community development block in the North 24 Parganas district of West Bengal, India, known for its riverine landscape and proximity to the Sundarbans region.
-
E.
Liaquatabad Town
Liaquatabad Town is a densely populated residential and commercial locality in Karachi, Pakistan, known for its bustling markets and central urban location.
- 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: Bangshal Triple: [Old Dhaka, contains, Bangshal]
Generated description
Bangshal is a historic, densely populated neighborhood in Old Dhaka, Bangladesh, known for its traditional markets and vibrant urban life.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bangshal Target entity description: Bangshal is a historic, densely populated neighborhood in Old Dhaka, Bangladesh, known for its traditional markets and vibrant urban life.
-
A.
Bangash
Bangash is a prominent Karlani Pashtun tribe historically settled in parts of present-day Pakistan and Afghanistan.
-
B.
Khanakul
Khanakul is a town in the Hooghly district of West Bengal, India, known for its rural setting and local agricultural economy.
-
C.
Bhangar
Bhangar is a town in the South 24 Parganas district of West Bengal, India, known for its semi-urban character and proximity to Kolkata.
-
D.
Sandeshkhali
Sandeshkhali is a rural town and community development block in the North 24 Parganas district of West Bengal, India, known for its riverine landscape and proximity to the Sundarbans region.
-
E.
Liaquatabad Town
Liaquatabad Town is a densely populated residential and commercial locality in Karachi, Pakistan, known for its bustling markets and central urban location.
- 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_69e0c46898008190aa618a4af55bd1ee |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef6c0cf6208190a8bd9fa423c65a40 |
completed | April 27, 2026, 2 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0a15a32c1c8190a9ae4efb9d09e1dc |
completed | May 17, 2026, 7:23 p.m. |
| NEDg | Description generation | batch_6a0a1635915081908c46794cdbaa4cde |
completed | May 17, 2026, 7:25 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0a16c70cfc81908125358316e2a89a |
completed | May 17, 2026, 7:28 p.m. |
Created at: April 16, 2026, 6:37 p.m.