Triple
T786455
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eastern Norway |
E16813
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Notodden
Notodden is a town and municipality in Vestfold og Telemark county, Norway, known for its industrial heritage and annual blues festival.
|
E116895
|
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: Notodden | Statement: [Eastern Norway, contains, Notodden]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Notodden Context triple: [Eastern Norway, contains, Notodden]
-
A.
Narvik
Narvik is a port town in northern Norway known for its strategic importance during World War II and as the site of major naval and land battles.
-
B.
Bodø
Bodø is a coastal city in northern Norway known as a regional hub for culture, transport, and access to Arctic nature.
-
C.
Skien
Skien is a historic city in southern Norway known as the birthplace of playwright Henrik Ibsen and as a regional commercial and industrial center.
-
D.
Porsgrunn
Porsgrunn is an industrial and port city in Telemark county in southeastern Norway, known for its porcelain production and location along the Telemark Canal.
-
E.
Kongsberg
Kongsberg is a Norwegian town known for its historic silver mines and its modern high-tech and defense industries.
- 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: Notodden Triple: [Eastern Norway, contains, Notodden]
Generated description
Notodden is a town and municipality in Vestfold og Telemark county, Norway, known for its industrial heritage and annual blues festival.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Notodden Target entity description: Notodden is a town and municipality in Vestfold og Telemark county, Norway, known for its industrial heritage and annual blues festival.
-
A.
Narvik
Narvik is a port town in northern Norway known for its strategic importance during World War II and as the site of major naval and land battles.
-
B.
Bodø
Bodø is a coastal city in northern Norway known as a regional hub for culture, transport, and access to Arctic nature.
-
C.
Skien
Skien is a historic city in southern Norway known as the birthplace of playwright Henrik Ibsen and as a regional commercial and industrial center.
-
D.
Porsgrunn
Porsgrunn is an industrial and port city in Telemark county in southeastern Norway, known for its porcelain production and location along the Telemark Canal.
-
E.
Kongsberg
Kongsberg is a Norwegian town known for its historic silver mines and its modern high-tech and defense industries.
- 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_69a4936cb7448190914f5fe4b8d81607 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a77fcc6881908a025bb21e44ad56 |
completed | March 1, 2026, 8:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac2578477c8190983de0a1065ad8ec |
completed | March 7, 2026, 1:17 p.m. |
| NEDg | Description generation | batch_69ac2668ca7481909c4babe382604df5 |
completed | March 7, 2026, 1:21 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ac26f947d481908ab1b7115cf9dee7 |
completed | March 7, 2026, 1:24 p.m. |
Created at: March 1, 2026, 7:38 p.m.