Triple
T19558309
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Solna strand metro station |
E489374
|
entity |
| Predicate | previousName |
P65
|
FINISHED |
| Object |
Vreten
Vreten was the former name of the Stockholm metro station now known as Solna strand, located in the municipality of Solna, Sweden.
|
E1384135
|
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: Vreten | Statement: [Solna strand metro station, previousName, Vreten]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vreten Context triple: [Solna strand metro station, previousName, Vreten]
-
A.
Veternica
Veternica is a river in Serbia that forms part of the Morava river basin.
-
B.
Vrély
Vrély is a small rural commune in the Somme department of northern France.
-
C.
Lypovets
Lypovets is a town in central Ukraine historically known as a local administrative and trade center.
-
D.
Vrasna
Vrasna is a coastal village in northern Greece known for its beaches and tourism, located within the regional unit of Thessaloniki.
-
E.
Vechigen
Vechigen is a rural municipality in the canton of Bern, Switzerland, known for its scattered settlements and agricultural landscape near the city of Bern.
- 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: Vreten Triple: [Solna strand metro station, previousName, Vreten]
Generated description
Vreten was the former name of the Stockholm metro station now known as Solna strand, located in the municipality of Solna, Sweden.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Vreten Target entity description: Vreten was the former name of the Stockholm metro station now known as Solna strand, located in the municipality of Solna, Sweden.
-
A.
Veternica
Veternica is a river in Serbia that forms part of the Morava river basin.
-
B.
Vrély
Vrély is a small rural commune in the Somme department of northern France.
-
C.
Lypovets
Lypovets is a town in central Ukraine historically known as a local administrative and trade center.
-
D.
Vrasna
Vrasna is a coastal village in northern Greece known for its beaches and tourism, located within the regional unit of Thessaloniki.
-
E.
Vechigen
Vechigen is a rural municipality in the canton of Bern, Switzerland, known for its scattered settlements and agricultural landscape near the city of Bern.
- 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_69d8e8dc5d8c8190a6d7bd8864f43ca0 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e63f723d5081909553a4363b579a6b |
completed | April 20, 2026, 3 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0757809d9c8190bf7651fc9425691e |
completed | May 15, 2026, 5:27 p.m. |
| NEDg | Description generation | batch_6a075b89f9d08190be3b14a4073fb570 |
completed | May 15, 2026, 5:44 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a075c02150c8190b26a3d58ee68b481 |
completed | May 15, 2026, 5:46 p.m. |
Created at: April 10, 2026, 1:42 p.m.