Triple
T15762842
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hemnes |
E382140
|
entity |
| Predicate | region |
P40
|
FINISHED |
| Object | Helgeland |
E388787
|
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: Helgeland | Statement: [Hemnes, region, Helgeland]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Helgeland Context triple: [Hemnes, region, Helgeland]
-
A.
Helgeland
chosen
Helgeland is a coastal region in northern Norway known for its dramatic fjords, islands, and mountain landscapes.
-
B.
Nordlandet
Nordlandet is one of the main islands and districts of the coastal Norwegian city of Kristiansund.
-
C.
Nordland
Nordland is a long coastal county in northern Norway known for its dramatic fjords, islands like the Lofoten archipelago, and Arctic landscapes.
-
D.
Nordre Land
Nordre Land is a rural municipality in Innlandet county, Norway, known for its forests, lakes, and agricultural landscape in the traditional district of Land.
-
E.
Hålogaland
Hålogaland is a historical region in northern Norway traditionally encompassing parts of what are now Troms and Nordland counties.
- 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_69d86d9e6b44819085d1f6a969ecb74c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e050b6c9fc8190a1bcf763c4b04b12 |
completed | April 16, 2026, 3 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01673979608190905afae3071413c0 |
completed | May 11, 2026, 5:20 a.m. |
Created at: April 10, 2026, 4:47 a.m.