Triple
T821755
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lillehammer |
E17762
|
entity |
| Predicate | hasDistrict |
P459
|
FINISHED |
| Object |
Søre Ål
Søre Ål is a residential district in the town of Lillehammer in Innlandet county, Norway.
|
E121231
|
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: Søre Ål | Statement: [Lillehammer, hasDistrict, Søre Ål]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Søre Ål Context triple: [Lillehammer, hasDistrict, Søre Ål]
-
A.
Drammenselva
Drammenselva is a major river in southeastern Norway known for its historical timber floating, hydroelectric power production, and salmon fishing.
-
B.
Randsfjorden
Randsfjorden is one of Norway’s largest inland lakes, located in Eastern Norway and known for its elongated shape and surrounding forested landscapes.
-
C.
Hjørundfjord
Hjørundfjord is a dramatic, narrow fjord in Norway’s Sunnmøre region, renowned for its steep mountain walls, deep waters, and scenic, relatively untouched natural landscapes.
-
D.
Glåmdalen
Glåmdalen is a valley region in Eastern Norway known for the Glomma River and its surrounding agricultural and forested landscapes.
-
E.
Sognefjord
Sognefjord is Norway’s longest and deepest fjord, renowned for its dramatic cliffs, glacial landscapes, and scenic coastal villages.
- 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: Søre Ål Triple: [Lillehammer, hasDistrict, Søre Ål]
Generated description
Søre Ål is a residential district in the town of Lillehammer in Innlandet county, Norway.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Søre Ål Target entity description: Søre Ål is a residential district in the town of Lillehammer in Innlandet county, Norway.
-
A.
Drammenselva
Drammenselva is a major river in southeastern Norway known for its historical timber floating, hydroelectric power production, and salmon fishing.
-
B.
Randsfjorden
Randsfjorden is one of Norway’s largest inland lakes, located in Eastern Norway and known for its elongated shape and surrounding forested landscapes.
-
C.
Hjørundfjord
Hjørundfjord is a dramatic, narrow fjord in Norway’s Sunnmøre region, renowned for its steep mountain walls, deep waters, and scenic, relatively untouched natural landscapes.
-
D.
Glåmdalen
Glåmdalen is a valley region in Eastern Norway known for the Glomma River and its surrounding agricultural and forested landscapes.
-
E.
Sognefjord
Sognefjord is Norway’s longest and deepest fjord, renowned for its dramatic cliffs, glacial landscapes, and scenic coastal villages.
- 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_69a4937bcaac8190a322524ac6f45a5a |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4ab7aea38819092a0860ec6e2a033 |
completed | March 1, 2026, 9:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac3b978de4819083b117ee3a6cb8c1 |
completed | March 7, 2026, 2:52 p.m. |
| NEDg | Description generation | batch_69ac3c9a92008190a6336626faed36bd |
completed | March 7, 2026, 2:56 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ac3d0fcdb88190b4c5e5ddf41e2716 |
completed | March 7, 2026, 2:58 p.m. |
Created at: March 1, 2026, 7:38 p.m.