Triple
T3687593
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bømlo |
E78261
|
entity |
| Predicate | connectedTo |
P37
|
FINISHED |
| Object | Stord |
E378635
|
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: Stord | Statement: [Bømlo, connectedTo, Stord]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stord Context triple: [Bømlo, connectedTo, Stord]
-
A.
Stord
chosen
Stord is a large island and municipality in Vestland county, western Norway, known for its industrial activity and location along major fjords and shipping routes.
-
B.
Sandefjord
Sandefjord is a coastal town and municipality in southern Norway known for its maritime heritage, whaling history, and popular seaside attractions.
-
C.
Skien
Skien is a historic city in southern Norway known as the birthplace of playwright Henrik Ibsen and as a regional commercial and industrial center.
-
D.
Storo
Storo is a neighborhood and transport hub in Oslo, Norway, known for its major shopping center and connections to tram, metro, and bus lines.
-
E.
Kristinestad
Kristinestad is a small coastal town in western Finland known for its well-preserved wooden old town and historic maritime character.
- 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_69b5b7446bf88190848eb7ecb0e067bd |
completed | March 14, 2026, 7:30 p.m. |
Created at: March 8, 2026, 3:26 p.m.