Triple
T5290828
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flytoget |
E119736
|
entity |
| Predicate | terminus |
P388
|
FINISHED |
| Object | Oslo S |
E150936
|
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: Oslo S | Statement: [Flytoget, terminus, Oslo S]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oslo S Context triple: [Flytoget, terminus, Oslo S]
-
A.
Osedalen
Osedalen is a village in Froland municipality in Agder county in southern Norway.
-
B.
Sarpsborg
Sarpsborg is a historic city and municipality in Viken county, Norway, known as one of the country’s oldest towns and an important industrial and administrative center in the Østfold region.
-
C.
OsloMet
OsloMet is a public university in Oslo, Norway, known for its professionally oriented programs and research in fields such as social sciences, health, technology, and education.
-
D.
Sentrum, Oslo
chosen
Sentrum is the central borough of Oslo, Norway, encompassing the city’s main downtown area, key commercial districts, and major transport hubs.
-
E.
Oslo
Oslo is the capital and largest city of Norway, known as a major cultural, economic, and governmental center.
- 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_69bd446de5648190b313a90bd96730d2 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd84eac7b88190900142bd1310c0fd |
completed | March 20, 2026, 5:33 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf06f066988190a3df7e270df84fdd |
completed | March 21, 2026, 9 p.m. |
Created at: March 20, 2026, 1:52 p.m.