Triple
T9886343
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Khulna Division |
E180941
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object |
Magura
Magura is a town and district headquarters in southwestern Bangladesh known for its agricultural surroundings and location within the Khulna Division.
|
E827974
|
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: Magura | Statement: [Khulna Division, containsCity, Magura]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Magura Context triple: [Khulna Division, containsCity, Magura]
-
A.
Mibuchi
Mibuchi is a Japanese surname borne by individuals such as Tadahiko Mibuchi.
-
B.
Yabu
Yabu is a small city in northern Hyōgo Prefecture, Japan, known for its rural landscapes, hot springs, and access to mountainous outdoor recreation.
-
C.
Binnig
Binnig is a German surname most notably associated with physicist Gerd Binnig, co-inventor of the scanning tunneling microscope and Nobel Prize laureate.
-
D.
Akashi
Akashi is a coastal city in western Japan known for its historic castle, views of the Akashi Kaikyō Strait, and its specialty dish akashiyaki.
-
E.
Mizumoto
Mizumoto is a neighborhood in Tokyo’s Katsushika ward, known for its large riverside Mizumoto Park and relatively green, residential environment.
- 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: Magura Triple: [Khulna Division, containsCity, Magura]
Generated description
Magura is a town and district headquarters in southwestern Bangladesh known for its agricultural surroundings and location within the Khulna Division.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Magura Target entity description: Magura is a town and district headquarters in southwestern Bangladesh known for its agricultural surroundings and location within the Khulna Division.
-
A.
Mibuchi
Mibuchi is a Japanese surname borne by individuals such as Tadahiko Mibuchi.
-
B.
Yabu
Yabu is a small city in northern Hyōgo Prefecture, Japan, known for its rural landscapes, hot springs, and access to mountainous outdoor recreation.
-
C.
Binnig
Binnig is a German surname most notably associated with physicist Gerd Binnig, co-inventor of the scanning tunneling microscope and Nobel Prize laureate.
-
D.
Akashi
Akashi is a coastal city in western Japan known for its historic castle, views of the Akashi Kaikyō Strait, and its specialty dish akashiyaki.
-
E.
Mizumoto
Mizumoto is a neighborhood in Tokyo’s Katsushika ward, known for its large riverside Mizumoto Park and relatively green, residential environment.
- 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_69ca828082cc8190a40f8d299caa6545 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cdb45659748190a3ebd1abe23c8779 |
completed | April 2, 2026, 12:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1eafc76b0819098e481bb17a3af2b |
completed | April 5, 2026, 4:54 a.m. |
| NEDg | Description generation | batch_69d1ecfce8588190815876afc7ec85d4 |
completed | April 5, 2026, 5:02 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d1ed99963881908dd14786a2e2e87f |
completed | April 5, 2026, 5:05 a.m. |
Created at: March 30, 2026, 8:38 p.m.