Triple
T16090587
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Operation Searchlight |
E390349
|
entity |
| Predicate | location |
P40
|
FINISHED |
| Object | Khulna |
E33023
|
NE FINISHED |
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: Khulna | Statement: [Operation Searchlight, location, Khulna]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Khulna Context triple: [Operation Searchlight, location, Khulna]
-
A.
Khulna
chosen
Khulna is a major industrial and port city in southwestern Bangladesh, situated on the Rupsha and Bhairab rivers and serving as a key gateway to the Sundarbans mangrove forest.
-
B.
Khulna District
Khulna District is an administrative region in southwestern Bangladesh known for its proximity to the Sundarbans mangrove forest and its role as an important industrial and riverine hub.
-
C.
Khulna Division
Khulna Division is an administrative region in southwestern Bangladesh known for the city of Khulna and its proximity to the Sundarbans mangrove forest.
-
D.
Chittagong
Chittagong is a major coastal city and Bangladesh’s principal seaport, known for its bustling maritime trade and industrial significance.
-
E.
Rangpur
Rangpur is a city in northern Bangladesh known as a regional administrative, cultural, and commercial center.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d87f198bc48190a8b7e53ca15b7ead |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e184522b2c8190986daae6cb2d9db4 |
completed | April 17, 2026, 12:52 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffeb934b448190a486401ac6c01065 |
completed | May 10, 2026, 2:21 a.m. |
Created at: April 10, 2026, 4:59 a.m.