Triple
T15030209
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Green line (Stockholm metro) |
E378322
|
entity |
| Predicate | hasTerminus |
P388
|
FINISHED |
| Object |
Hässelby gård
Hässelby gård is a residential district and Stockholm metro station in western Stockholm, Sweden, served by the Green line.
|
E1134020
|
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: Hässelby gård | Statement: [Green line (Stockholm metro), hasTerminus, Hässelby gård]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hässelby gård Context triple: [Green line (Stockholm metro), hasTerminus, Hässelby gård]
-
A.
Häggenås
Häggenås is a small locality in Jämtland County, northern Sweden, situated within Östersund Municipality.
-
B.
Rosengård
Rosengård is a prominent Swedish football club based in Malmö, known for its successful women's team and history of developing world-class players.
-
C.
Grubbegata
Grubbegata is a street in central Oslo, Norway, known for running through the area that houses key government buildings and institutions.
-
D.
Humlegården
Humlegården is a large historic park in central Stockholm known for its green spaces, walking paths, and recreational areas.
-
E.
Djursholm
Djursholm is an affluent suburban district of Stockholm, Sweden, known for its villas, garden-city planning, and status as one of the country’s wealthiest residential areas.
- 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: Hässelby gård Triple: [Green line (Stockholm metro), hasTerminus, Hässelby gård]
Generated description
Hässelby gård is a residential district and Stockholm metro station in western Stockholm, Sweden, served by the Green line.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hässelby gård Target entity description: Hässelby gård is a residential district and Stockholm metro station in western Stockholm, Sweden, served by the Green line.
-
A.
Häggenås
Häggenås is a small locality in Jämtland County, northern Sweden, situated within Östersund Municipality.
-
B.
Rosengård
Rosengård is a prominent Swedish football club based in Malmö, known for its successful women's team and history of developing world-class players.
-
C.
Grubbegata
Grubbegata is a street in central Oslo, Norway, known for running through the area that houses key government buildings and institutions.
-
D.
Humlegården
Humlegården is a large historic park in central Stockholm known for its green spaces, walking paths, and recreational areas.
-
E.
Djursholm
Djursholm is an affluent suburban district of Stockholm, Sweden, known for its villas, garden-city planning, and status as one of the country’s wealthiest residential areas.
- 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_69d85cd46b2c819090d054c27787f677 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded7e2416081908dfba48d7f7b4a84 |
completed | April 15, 2026, 12:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe9dd967588190821cf47e9734db21 |
completed | May 9, 2026, 2:37 a.m. |
| NEDg | Description generation | batch_69fe9e5dbbe0819084567688758b0245 |
completed | May 9, 2026, 2:39 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fe9eedca1481908ce438991184d62e |
completed | May 9, 2026, 2:41 a.m. |
Created at: April 10, 2026, 2:59 a.m.