Triple
T2206788
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fredriksten fortress |
E50817
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Halden |
E9275
|
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: Halden | Statement: [Fredriksten fortress, locatedIn, Halden]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Halden Context triple: [Fredriksten fortress, locatedIn, Halden]
-
A.
Halden
chosen
Halden is a historic border town and municipality in southeastern Norway, known for the Fredriksten fortress and its location near the Swedish border.
-
B.
Drammen
Drammen is a city and municipality in southeastern Norway known for its riverside setting along the Drammenselva and its role as a regional commercial and transport hub.
-
C.
Sinsen
Sinsen is a neighborhood and major transport hub in Oslo, Norway, known for its busy traffic interchange and public transit connections.
-
D.
Tjuvholmen
Tjuvholmen is a modern waterfront district in central Oslo known for its contemporary architecture, art galleries, and seaside promenade.
-
E.
Kjelsås
Kjelsås is a residential neighborhood in northern Oslo, Norway, known for its hilly terrain, proximity to Marka forest, and access to the city via tram and rail connections.
- 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_69a88b06709c8190978fb2418470d1b6 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abbfcbb83081908d5b2f1603c7b4d2 |
completed | March 7, 2026, 6:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae654b89b081908f8c8b9bfc0b6579 |
completed | March 9, 2026, 6:14 a.m. |
Created at: March 4, 2026, 7:46 p.m.