Triple
T20114268
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Strømsø |
E490412
|
entity |
| Predicate | hasNearbyDistrict |
P4647
|
FINISHED |
| Object |
Gulskogen
Gulskogen is a residential district in Drammen, Norway, known for its historic manor house and surrounding park.
|
E1411257
|
NE FINISHED |
How this triple was built (4 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: Gulskogen | Statement: [Strømsø, hasNearbyDistrict, Gulskogen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gulskogen Context triple: [Strømsø, hasNearbyDistrict, Gulskogen]
-
A.
Kvamskogen
Kvamskogen is a popular mountainous recreational area in western Norway known for its ski resorts, cabins, and outdoor activities.
-
B.
Skogås
Skogås is a suburban district in the southern Stockholm area of Sweden, known primarily as a residential community with good commuter connections to central Stockholm.
-
C.
Lill-Jansskogen
Lill-Jansskogen is a large urban forest and recreational park area in Stockholm, Sweden, popular for walking, running, and outdoor activities.
-
D.
Fältskog
Fältskog is a Swedish surname most famously borne by Agnetha Fältskog, the singer from the pop group ABBA.
-
E.
Krokskogen
Krokskogen is a large forested area and popular outdoor recreation region in southeastern Norway, known for its hiking and skiing trails between Oslo and the Ringerike district.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Gulskogen Triple: [Strømsø, hasNearbyDistrict, Gulskogen]
Generated description
Gulskogen is a residential district in Drammen, Norway, known for its historic manor house and surrounding park.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Gulskogen Target entity description: Gulskogen is a residential district in Drammen, Norway, known for its historic manor house and surrounding park.
-
A.
Kvamskogen
Kvamskogen is a popular mountainous recreational area in western Norway known for its ski resorts, cabins, and outdoor activities.
-
B.
Skogås
Skogås is a suburban district in the southern Stockholm area of Sweden, known primarily as a residential community with good commuter connections to central Stockholm.
-
C.
Lill-Jansskogen
Lill-Jansskogen is a large urban forest and recreational park area in Stockholm, Sweden, popular for walking, running, and outdoor activities.
-
D.
Fältskog
Fältskog is a Swedish surname most famously borne by Agnetha Fältskog, the singer from the pop group ABBA.
-
E.
Krokskogen
Krokskogen is a large forested area and popular outdoor recreation region in southeastern Norway, known for its hiking and skiing trails between Oslo and the Ringerike district.
- F. None of above. chosen
Provenance (5 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_69da62636cc08190982cc71733a17b8d |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e666e31af081908d8e0c867c388a73 |
completed | April 20, 2026, 5:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a08271c02b481908131cf1afc7ab027 |
completed | May 16, 2026, 8:13 a.m. |
| NEDg | Description generation | batch_6a082800b084819089a32a683d59f9d9 |
completed | May 16, 2026, 8:17 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0828572b088190abcbbdfb568b3c9d |
completed | May 16, 2026, 8:18 a.m. |
Created at: April 11, 2026, 11:29 p.m.