Triple
T13042062
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Iveland |
E327217
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object |
Vatnestrøm
Vatnestrøm is a small village in the municipality of Iveland in Agder county, southern Norway.
|
E1017668
|
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: Vatnestrøm | Statement: [Iveland, containsSettlement, Vatnestrøm]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vatnestrøm Context triple: [Iveland, containsSettlement, Vatnestrøm]
-
A.
Icelandic River
The Icelandic River is a waterway in Manitoba, Canada, that flows through communities such as Riverton and ultimately drains into Lake Winnipeg.
-
B.
Vesle
The Vesle is a river in northeastern France that flows through the Champagne region and was a significant geographic feature during World War I battles.
-
C.
Veddesta
Veddesta is an industrial and commercial area in Järfälla Municipality, northwest of central Stockholm, Sweden.
-
D.
Jökulsá á Fjöllum
Jökulsá á Fjöllum is one of Iceland’s largest glacial rivers, known for flowing north from the Vatnajökull region through dramatic canyons and feeding the powerful Dettifoss waterfall.
-
E.
Strømmen
Strømmen is a town in Lillestrøm municipality in Viken county, Norway, known for its shopping mall Strømmen Storsenter and its historical industrial and railway heritage.
- 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: Vatnestrøm Triple: [Iveland, containsSettlement, Vatnestrøm]
Generated description
Vatnestrøm is a small village in the municipality of Iveland in Agder county, southern Norway.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Vatnestrøm Target entity description: Vatnestrøm is a small village in the municipality of Iveland in Agder county, southern Norway.
-
A.
Icelandic River
The Icelandic River is a waterway in Manitoba, Canada, that flows through communities such as Riverton and ultimately drains into Lake Winnipeg.
-
B.
Vesle
The Vesle is a river in northeastern France that flows through the Champagne region and was a significant geographic feature during World War I battles.
-
C.
Veddesta
Veddesta is an industrial and commercial area in Järfälla Municipality, northwest of central Stockholm, Sweden.
-
D.
Jökulsá á Fjöllum
Jökulsá á Fjöllum is one of Iceland’s largest glacial rivers, known for flowing north from the Vatnajökull region through dramatic canyons and feeding the powerful Dettifoss waterfall.
-
E.
Strømmen
Strømmen is a town in Lillestrøm municipality in Viken county, Norway, known for its shopping mall Strømmen Storsenter and its historical industrial and railway heritage.
- 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_69d8076e64308190904fb5c93517c901 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d9804f0318819081516e2ca1de6797 |
completed | April 10, 2026, 10:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6cbd5139c8190aaec6487f074f251 |
completed | May 3, 2026, 4:15 a.m. |
| NEDg | Description generation | batch_69f6ce6278e081908864fba1db23ada0 |
completed | May 3, 2026, 4:26 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6cf547b188190b24c51e06a3b4d3c |
completed | May 3, 2026, 4:30 a.m. |
Created at: April 9, 2026, 8:56 p.m.