Triple
T15448167
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brumunddal |
E370077
|
entity |
| Predicate | hasRiver |
P165
|
FINISHED |
| Object |
Brumunda
Brumunda is a river in Innlandet county, Norway, flowing through the town of Brumunddal before reaching Lake Mjøsa.
|
E1157163
|
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: Brumunda | Statement: [Brumunddal, hasRiver, Brumunda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brumunda Context triple: [Brumunddal, hasRiver, Brumunda]
-
A.
Breuci
The Breuci were an ancient Illyrian tribe known for their significant role in resisting Roman rule during major uprisings in the Balkans.
-
B.
Bruparck
Bruparck is a leisure and entertainment complex in Brussels that includes attractions such as theme parks, cinemas, and the miniature park Mini-Europe.
-
C.
Frunze
Frunze is a surname most notably associated with Mikhail Frunze, a prominent Bolshevik leader and Red Army commander during the Russian Civil War.
-
D.
Bumba
Bumba is a Romanian professional footballer known for playing as an attacking midfielder and winger for various clubs in Europe.
-
E.
Breng
Breng is a Dutch public transport operator providing regional bus and train services in and around Arnhem and Nijmegen in the Netherlands.
- 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: Brumunda Triple: [Brumunddal, hasRiver, Brumunda]
Generated description
Brumunda is a river in Innlandet county, Norway, flowing through the town of Brumunddal before reaching Lake Mjøsa.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Brumunda Target entity description: Brumunda is a river in Innlandet county, Norway, flowing through the town of Brumunddal before reaching Lake Mjøsa.
-
A.
Breuci
The Breuci were an ancient Illyrian tribe known for their significant role in resisting Roman rule during major uprisings in the Balkans.
-
B.
Bruparck
Bruparck is a leisure and entertainment complex in Brussels that includes attractions such as theme parks, cinemas, and the miniature park Mini-Europe.
-
C.
Frunze
Frunze is a surname most notably associated with Mikhail Frunze, a prominent Bolshevik leader and Red Army commander during the Russian Civil War.
-
D.
Bumba
Bumba is a Romanian professional footballer known for playing as an attacking midfielder and winger for various clubs in Europe.
-
E.
Breng
Breng is a Dutch public transport operator providing regional bus and train services in and around Arnhem and Nijmegen in the Netherlands.
- 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_69d85a19180081909925012fbf4e62a3 |
completed | April 10, 2026, 2:02 a.m. |
| NER | Named-entity recognition | batch_69e03ef767b4819099f2c0919a158321 |
completed | April 16, 2026, 1:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff21afb6f4819094162ca842b7eb60 |
completed | May 9, 2026, 11:59 a.m. |
| NEDg | Description generation | batch_69ff22a9429081909724f248da07e24a |
completed | May 9, 2026, 12:03 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff2339ae808190bf2d4676215399c0 |
completed | May 9, 2026, 12:06 p.m. |
Created at: April 10, 2026, 3:21 a.m.