Triple
T1837062
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Finnish Navy |
E41089
|
entity |
| Predicate | garrison |
P75
|
FINISHED |
| Object |
Kokkola
Kokkola is a coastal city in western Finland known for its maritime heritage and role as a military and naval hub.
|
E280624
|
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: Kokkola | Statement: [Finnish Navy, garrison, Kokkola]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kokkola Context triple: [Finnish Navy, garrison, Kokkola]
-
A.
Lappeenranta
Lappeenranta is a city in southeastern Finland near the Russian border, known for its lakeside location on Saimaa and its role as a regional commercial and educational center.
-
B.
Pori
Pori is a coastal city in western Finland known for its industrial heritage, port, and annual Pori Jazz Festival.
-
C.
Lahti
Lahti is a city in southern Finland known for its winter sports facilities, particularly ski jumping and cross-country skiing, and for hosting numerous international sporting events.
-
D.
Imatra
Imatra is a town and municipality in southeastern Finland known for its industrial history, proximity to the Russian border, and the Imatrankoski rapids.
-
E.
Joensuu
Joensuu is a city in eastern Finland that serves as a regional center for North Karelia, known for its university, forestry industry, and proximity to lakes and forests.
- 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: Kokkola Triple: [Finnish Navy, garrison, Kokkola]
Generated description
Kokkola is a coastal city in western Finland known for its maritime heritage and role as a military and naval hub.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kokkola Target entity description: Kokkola is a coastal city in western Finland known for its maritime heritage and role as a military and naval hub.
-
A.
Lappeenranta
Lappeenranta is a city in southeastern Finland near the Russian border, known for its lakeside location on Saimaa and its role as a regional commercial and educational center.
-
B.
Pori
Pori is a coastal city in western Finland known for its industrial heritage, port, and annual Pori Jazz Festival.
-
C.
Lahti
Lahti is a city in southern Finland known for its winter sports facilities, particularly ski jumping and cross-country skiing, and for hosting numerous international sporting events.
-
D.
Imatra
Imatra is a town and municipality in southeastern Finland known for its industrial history, proximity to the Russian border, and the Imatrankoski rapids.
-
E.
Joensuu
Joensuu is a city in eastern Finland that serves as a regional center for North Karelia, known for its university, forestry industry, and proximity to lakes and forests.
- 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_69a88647f9388190909bc36e795bdaec |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb0380a4c81909a2ad0bfd97c884a |
completed | March 7, 2026, 4:57 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af8336f98c8190949c0145d2d31a8f |
completed | March 10, 2026, 2:34 a.m. |
| NEDg | Description generation | batch_69af840b2fb881909755b06563b8c561 |
completed | March 10, 2026, 2:38 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69af8487bcac819085b6f5827a48696a |
completed | March 10, 2026, 2:40 a.m. |
Created at: March 4, 2026, 7:33 p.m.