Triple
T5290857
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flytoget |
E119736
|
entity |
| Predicate | stationServed |
P6301
|
FINISHED |
| Object | Asker |
E125781
|
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: Asker | Statement: [Flytoget, stationServed, Asker]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Asker Context triple: [Flytoget, stationServed, Asker]
-
A.
Asker
chosen
Asker is a municipality in Viken county, Norway, known for its coastal location near Oslo and its mix of residential areas, cultural sites, and natural landscapes.
-
B.
Askeran
Askeran is a town in the disputed Nagorno-Karabakh region of the South Caucasus, historically known for its strategic location and fortress.
-
C.
Aske
Aske is a surname of Scandinavian origin borne by various individuals, including those with the given name Ellen.
-
D.
Andselv
Andselv is a small Norwegian village located in the Troms region, known for its position along the Andselva river and proximity to Bardufoss.
-
E.
Askim
Askim is a town in southeastern Norway that serves as one of the locations for Østfold University College’s campuses.
- 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.