Triple
T3145056
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Innlandet |
E65742
|
entity |
| Predicate | containsLake |
P1025
|
FINISHED |
| Object | Mjøsa |
E65750
|
NE FINISHED |
How this triple was built (2 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: Mjøsa | Statement: [Innlandet, containsLake, Mjøsa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mjøsa Context triple: [Innlandet, containsLake, Mjøsa]
-
A.
Mjøsa Lake
chosen
Mjøsa Lake is Norway’s largest lake, located in the southeastern part of the country and known for its scenic surroundings and historic towns along its shores.
-
B.
Øymarksjøen
Øymarksjøen is a lake in southeastern Norway known for its forested surroundings, recreational fishing, and role in the local waterway system near the Swedish border.
-
C.
Sognsvann
Sognsvann is a popular recreational lake and surrounding forested area in northern Oslo, Norway, known for hiking, swimming, and outdoor activities.
-
D.
Sjusjøen
Sjusjøen is a popular Norwegian cross-country skiing destination and mountain village known for its extensive trail network and scenic highland landscapes near Lillehammer.
-
E.
Trondheimsfjord
Trondheimsfjord is a major Norwegian fjord on the central coast, known for its deep waters, rich marine life, and the city of Trondheim along its shores.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ad8582f564819088c27e1f96153938 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada595d4548190b720a6131817833b |
completed | March 8, 2026, 4:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b224ed4d748190a2af68bf284110e8 |
completed | March 12, 2026, 2:29 a.m. |
Created at: March 8, 2026, 3:05 p.m.