Triple
T3189692
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Svealand |
E66788
|
entity |
| Predicate | containsLake |
P1025
|
FINISHED |
| Object | Lake Mälaren |
E95397
|
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: Lake Mälaren | Statement: [Svealand, containsLake, Lake Mälaren]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lake Mälaren Context triple: [Svealand, containsLake, Lake Mälaren]
-
A.
Lake Mälaren
chosen
Lake Mälaren is a large freshwater lake in eastern Sweden that connects to the Baltic Sea and has Stockholm situated on its shores.
-
B.
Lake Vättern
Lake Vättern is Sweden’s second-largest lake, a deep, elongated freshwater body in south-central Sweden known for its clear waters and surrounding historic towns.
-
C.
Lake Vänern
Lake Vänern is Sweden’s largest lake and one of Europe’s biggest freshwater lakes, known for its extensive archipelagos and important role in regional ecology and transportation.
-
D.
Storsjön
Storsjön is a large lake in central Sweden, famed for its scenic surroundings and the local legend of the lake monster Storsjöodjuret.
-
E.
Munksjön
Munksjön is a small urban lake situated in central Jönköping in southern Sweden, known for its promenades, recreational areas, and proximity to the city’s downtown.
- 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_69ad8587c1bc8190a2595f2c22ee1001 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada6e67e948190afbd9cc6a3ade415 |
completed | March 8, 2026, 4:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b262126fa08190b7dd620159e3ed96 |
completed | March 12, 2026, 6:49 a.m. |
Created at: March 8, 2026, 3:07 p.m.