Triple
T20646491
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pabna Mental Hospital |
E507367
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Pabna town |
—
|
NE NERFINISHED |
How this triple was built (2 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: Pabna town | Statement: [Pabna Mental Hospital, near, Pabna town]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pabna town Context triple: [Pabna Mental Hospital, near, Pabna town]
-
A.
Pabna
chosen
Pabna is a town and district in present-day Bangladesh, historically part of British India's Bengal region and known for its role in agrarian movements and regional administration.
-
B.
Jamalpur
Jamalpur is a city in central Bangladesh known as an important regional hub for agriculture and trade near the Jamuna River.
-
C.
Pabna District
Pabna District is an administrative region in western Bangladesh known for its fertile agricultural land, growing industrial sector, and location along major rivers.
-
D.
Bhabanipur
Bhabanipur is an urban legislative assembly constituency in Kolkata, West Bengal, known for being represented by prominent political leader Mamata Banerjee.
-
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.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4be702c8190a3d2410a881d310a |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6af1eee9c81908fd3b4fe8c4529c8 |
completed | April 20, 2026, 10:56 p.m. |
Created at: April 16, 2026, 11:43 a.m.