Triple
T7541542
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gästrikland |
E178285
|
entity |
| Predicate | hasTown |
P847
|
FINISHED |
| Object |
Sandviken
Sandviken is an industrial town in central Sweden, best known as the historic home of the steel company Sandvik.
|
E672785
|
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: Sandviken | Statement: [Gästrikland, hasTown, Sandviken]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sandviken Context triple: [Gästrikland, hasTown, Sandviken]
-
A.
Söderort
Söderort is the southern suburban part of Stockholm, Sweden, consisting mainly of residential districts located south of the inner-city island of Södermalm.
-
B.
Fredrikshamn
Fredrikshamn (Hamina) is a coastal town in southeastern Finland that historically served as an important military and trading center.
-
C.
Hjulsta
Hjulsta is a suburb in northwestern Stockholm, Sweden, known for being the terminus of one of the Stockholm metro lines.
-
D.
Strömstad
Strömstad is a coastal town and municipality in western Sweden, near the Norwegian border, known for its archipelago, tourism, and ferry connections.
-
E.
Vänersborg
Vänersborg is a Swedish town located at the southern tip of Lake Vänern, known historically as an administrative and trading center.
- 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: Sandviken Triple: [Gästrikland, hasTown, Sandviken]
Generated description
Sandviken is an industrial town in central Sweden, best known as the historic home of the steel company Sandvik.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sandviken Target entity description: Sandviken is an industrial town in central Sweden, best known as the historic home of the steel company Sandvik.
-
A.
Söderort
Söderort is the southern suburban part of Stockholm, Sweden, consisting mainly of residential districts located south of the inner-city island of Södermalm.
-
B.
Fredrikshamn
Fredrikshamn (Hamina) is a coastal town in southeastern Finland that historically served as an important military and trading center.
-
C.
Hjulsta
Hjulsta is a suburb in northwestern Stockholm, Sweden, known for being the terminus of one of the Stockholm metro lines.
-
D.
Strömstad
Strömstad is a coastal town and municipality in western Sweden, near the Norwegian border, known for its archipelago, tourism, and ferry connections.
-
E.
Vänersborg
Vänersborg is a Swedish town located at the southern tip of Lake Vänern, known historically as an administrative and trading center.
- 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_69c69f2be3888190a6667a27f8f195e9 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f8750f80819088ddfb7a5580b5df |
completed | March 27, 2026, 9:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c856b93188819080c769a2a1b122f4 |
completed | March 28, 2026, 10:31 p.m. |
| NEDg | Description generation | batch_69c857738e6881908abfce108d71efc0 |
completed | March 28, 2026, 10:34 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c857e4a0408190b395389c6221e259 |
completed | March 28, 2026, 10:36 p.m. |
Created at: March 27, 2026, 3:48 p.m.