Triple
T16811940
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Østre Toten |
E408635
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object |
Lensbygda
Lensbygda is a small village in Innlandet county, Norway, situated within the rural municipality of Østre Toten.
|
E1235172
|
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: Lensbygda | Statement: [Østre Toten, containsSettlement, Lensbygda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lensbygda Context triple: [Østre Toten, containsSettlement, Lensbygda]
-
A.
Lensvik
Lensvik is a small village in Trøndelag county, Norway, situated along the Trondheimsfjord and known historically for its fruit cultivation.
-
B.
Lessebo
Lessebo is a small locality and municipality in southern Sweden known for its traditional paper mill and glassmaking heritage.
-
C.
Lierbyen
Lierbyen is a village in Buskerud county, Norway, serving as the main local hub for commerce and public services in the municipality of Lier.
-
D.
Teigebyen
Teigebyen is a village in Viken county, Norway, serving as the main local hub for municipal services and community life in Nannestad.
-
E.
Nesbyen
Nesbyen is a small town and municipality in southeastern Norway known for its inland valley setting, historic wooden buildings, and notably warm summer temperatures.
- 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: Lensbygda Triple: [Østre Toten, containsSettlement, Lensbygda]
Generated description
Lensbygda is a small village in Innlandet county, Norway, situated within the rural municipality of Østre Toten.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lensbygda Target entity description: Lensbygda is a small village in Innlandet county, Norway, situated within the rural municipality of Østre Toten.
-
A.
Lensvik
Lensvik is a small village in Trøndelag county, Norway, situated along the Trondheimsfjord and known historically for its fruit cultivation.
-
B.
Lessebo
Lessebo is a small locality and municipality in southern Sweden known for its traditional paper mill and glassmaking heritage.
-
C.
Lierbyen
Lierbyen is a village in Buskerud county, Norway, serving as the main local hub for commerce and public services in the municipality of Lier.
-
D.
Teigebyen
Teigebyen is a village in Viken county, Norway, serving as the main local hub for municipal services and community life in Nannestad.
-
E.
Nesbyen
Nesbyen is a small town and municipality in southeastern Norway known for its inland valley setting, historic wooden buildings, and notably warm summer temperatures.
- 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_69d88393905081908d00a86b99996ac8 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3b2d0793c81909d938ac174a6e63a |
completed | April 18, 2026, 4:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00b292a5888190812539b14eb77f34 |
completed | May 10, 2026, 4:30 p.m. |
| NEDg | Description generation | batch_6a00b32d2a588190b59bad56f8817bce |
completed | May 10, 2026, 4:32 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a00b3d14b3c819081f435777f47eca3 |
completed | May 10, 2026, 4:35 p.m. |
Created at: April 10, 2026, 5:23 a.m.