Triple
T18113877
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Steinberg |
E433549
|
entity |
| Predicate | locatedInValley |
P40
|
FINISHED |
| Object | Drammensdalen |
—
|
NE NERFINISHED |
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: Drammensdalen | Statement: [Steinberg, locatedInValley, Drammensdalen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Drammensdalen Context triple: [Steinberg, locatedInValley, Drammensdalen]
-
A.
Drammensdalen
chosen
Drammensdalen is a valley in southeastern Norway known for the Drammenselva river and its role as a populated transport corridor between inland areas and the Oslofjord region.
-
B.
Groruddalen
Groruddalen is a large valley and suburban area in the northeastern part of Oslo, Norway, known for its diverse population and extensive residential neighborhoods.
-
C.
Fyllingsdalen
Fyllingsdalen is a borough of Bergen, Norway, known as a residential district located southwest of the city center.
-
D.
Sogndalsdalen
Sogndalsdalen is a scenic valley in western Norway known for its dramatic landscapes, rivers, and access to hiking and outdoor activities.
-
E.
Nydalen
Nydalen is a modern riverside neighborhood in Oslo, Norway, known for its business district, educational institutions, and redeveloped industrial areas.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b90916008190a1f110bd7ced5473 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4ddd4c7888190b85c39decdb0333f |
completed | April 19, 2026, 1:51 p.m. |
Created at: April 10, 2026, 10:28 a.m.