Triple
T1335947
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Einar Gerhardsen |
E28748
|
entity |
| Predicate | placeOfBirth |
P1
|
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: [Einar Gerhardsen, placeOfBirth, Asker]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Asker Context triple: [Einar Gerhardsen, placeOfBirth, 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.
Askim
Askim is a town in southeastern Norway that serves as one of the locations for Østfold University College’s campuses.
-
C.
Ullensaker
Ullensaker is a municipality in Viken county, Norway, best known for hosting Oslo Airport, Gardermoen, the country’s main international airport.
-
D.
Kongsvinger
Kongsvinger is a town and municipality in Innlandet county, Norway, known for its historic fortress overlooking the Glomma River and its role as a regional center near the Swedish border.
-
E.
Helleren
Helleren is a small historic settlement in Norway known for its traditional houses built under a large rock overhang near the Jøssingfjord.
- 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_69a498561a508190a3e1bc137c2b866a |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c1ecb5208190a9eadda113c91e66 |
completed | March 1, 2026, 10:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69acc62b9bd081909dbe22cbea03f21f |
completed | March 8, 2026, 12:43 a.m. |
Created at: March 1, 2026, 7:55 p.m.