Triple
T3687600
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bømlo |
E78261
|
entity |
| Predicate | previouslyPartOf |
P5057
|
FINISHED |
| Object | Hordaland county |
E366605
|
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: Hordaland county | Statement: [Bømlo, previouslyPartOf, Hordaland county]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hordaland county Context triple: [Bømlo, previouslyPartOf, Hordaland county]
-
A.
Hordaland
chosen
Hordaland was a former county in western Norway known for its fjords, coastal landscapes, and the city of Bergen.
-
B.
Rogaland
Rogaland is a county in southwestern Norway known for its rugged coastline, fjords, and the oil industry centered around the city of Stavanger.
-
C.
Sogn og Fjordane
Sogn og Fjordane was a former county in western Norway known for its dramatic fjords, mountains, and coastal landscapes.
-
D.
Hedmark
Hedmark is a former county in eastern Norway known for its vast forests, agriculture, and inland landscapes along the Swedish border.
-
E.
Hedmarken
Hedmarken is a traditional district in Innlandet county in eastern Norway, known for its agricultural landscapes and its central town, Hamar.
- 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_69ad85e285a081908f8cbfa9e2ed9b75 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc4c7e2bc81909356c8b0ed90feed |
completed | March 8, 2026, 6:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b6131d07048190bbc735cf88d5ee60 |
completed | March 15, 2026, 2:02 a.m. |
Created at: March 8, 2026, 3:26 p.m.