Triple
T10450617
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Akershus county |
E246411
|
entity |
| Predicate | bordered |
P224
|
FINISHED |
| Object | Hedmark county |
E102451
|
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: Hedmark county | Statement: [Akershus county, bordered, Hedmark county]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hedmark county Context triple: [Akershus county, bordered, Hedmark county]
-
A.
Hedmark
chosen
Hedmark is a former county in eastern Norway known for its vast forests, agriculture, and inland landscapes along the Swedish border.
-
B.
Hedmarken
Hedmarken is a traditional district in Innlandet county in eastern Norway, known for its agricultural landscapes and its central town, Hamar.
-
C.
Akershus county
Akershus county was a former county in southeastern Norway that historically surrounded Oslo and included both urban suburbs and rural areas before being merged into Viken county.
-
D.
Oslo county
Oslo county is Norway’s capital county, encompassing the city of Oslo and serving as the country’s political, economic, and cultural center.
-
E.
Telemark county
Telemark county was a former county in southeastern Norway known for its rich folk culture, traditional architecture, and varied landscape of mountains, forests, and coastal areas.
- 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_69d381c04fe08190957c26c526a3b05a |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4fe0a6a548190a54212912f618e4e |
completed | April 7, 2026, 12:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e37382a0bc81908938b3cbdf0528e0 |
completed | April 18, 2026, 12:05 p.m. |
Created at: April 6, 2026, 12:17 p.m.