Triple
T9815424
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sakarya Province |
E238390
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object |
Karasu
Karasu is a coastal town and district in northwestern Turkey known for its Black Sea beaches and location within Sakarya Province.
|
E823353
|
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: Karasu | Statement: [Sakarya Province, hasCity, Karasu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Karasu Context triple: [Sakarya Province, hasCity, Karasu]
-
A.
Karasuwa
Karasuwa is a local government area in northeastern Nigeria known for its predominantly rural communities and agricultural activities within Yobe State.
-
B.
Aokas
Aokas is a coastal town in northern Algeria known for its Mediterranean beaches, karst caves, and location along the scenic shoreline of Béjaïa Province.
-
C.
Tsubame
Tsubame is a Japanese Shinkansen train service that operates on the Kyushu Shinkansen line in southern Japan.
-
D.
Waras
Waras is a significant town in Afghanistan’s central highland region of Hazarajat, serving as an important local hub for the surrounding Hazara communities.
-
E.
Kogarah
Kogarah is a suburb in southern Sydney, New South Wales, Australia, known as a residential and commercial hub in the St George area.
- 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: Karasu Triple: [Sakarya Province, hasCity, Karasu]
Generated description
Karasu is a coastal town and district in northwestern Turkey known for its Black Sea beaches and location within Sakarya Province.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Karasu Target entity description: Karasu is a coastal town and district in northwestern Turkey known for its Black Sea beaches and location within Sakarya Province.
-
A.
Karasuwa
Karasuwa is a local government area in northeastern Nigeria known for its predominantly rural communities and agricultural activities within Yobe State.
-
B.
Aokas
Aokas is a coastal town in northern Algeria known for its Mediterranean beaches, karst caves, and location along the scenic shoreline of Béjaïa Province.
-
C.
Tsubame
Tsubame is a Japanese Shinkansen train service that operates on the Kyushu Shinkansen line in southern Japan.
-
D.
Waras
Waras is a significant town in Afghanistan’s central highland region of Hazarajat, serving as an important local hub for the surrounding Hazara communities.
-
E.
Kogarah
Kogarah is a suburb in southern Sydney, New South Wales, Australia, known as a residential and commercial hub in the St George area.
- 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_69ca84dfde1481909f47c286d715f892 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb2f341648190bf8343e1124085cb |
completed | April 2, 2026, 12:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1cc6c64dc8190979be34255dc22e5 |
completed | April 5, 2026, 2:43 a.m. |
| NEDg | Description generation | batch_69d1cf7ce46c8190a7383086eb667b51 |
completed | April 5, 2026, 2:57 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d1d0034dc081908182e3f873a2c584 |
completed | April 5, 2026, 2:59 a.m. |
Created at: March 30, 2026, 8:30 p.m.