Triple
T20649743
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mörby |
E507456
|
entity |
| Predicate | servedBy |
P82
|
FINISHED |
| Object |
Mörby station
Mörby station is a public transit stop in Mörby, Sweden, functioning as a local hub for commuter travel in the area.
|
E1444343
|
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: Mörby station | Statement: [Mörby, servedBy, Mörby station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mörby station Context triple: [Mörby, servedBy, Mörby station]
-
A.
Gulskogen Station
Gulskogen Station is a railway station in the Drammen area of Viken county, Norway, serving local and regional train traffic.
-
B.
Märsta Station
Märsta Station is a key suburban railway hub in the town of Märsta, serving as a northern terminus and important node in the Stockholm commuter rail network.
-
C.
Östberga station
Östberga station is a local railway stop serving the suburban area of Djursholm in the Stockholm metropolitan region of Sweden.
-
D.
Skogen station
Skogen station is a small metro stop on Oslo’s Holmenkollen Line (Line 1), serving the hillside residential area of Skogen in the Vestre Aker district.
-
E.
Högberga station
Högberga station is a local stop on the Lidingöbanan light rail line serving the Högberga area on Lidingö Island near Stockholm, Sweden.
- 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: Mörby station Triple: [Mörby, servedBy, Mörby station]
Generated description
Mörby station is a public transit stop in Mörby, Sweden, functioning as a local hub for commuter travel in the area.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mörby station Target entity description: Mörby station is a public transit stop in Mörby, Sweden, functioning as a local hub for commuter travel in the area.
-
A.
Gulskogen Station
Gulskogen Station is a railway station in the Drammen area of Viken county, Norway, serving local and regional train traffic.
-
B.
Märsta Station
Märsta Station is a key suburban railway hub in the town of Märsta, serving as a northern terminus and important node in the Stockholm commuter rail network.
-
C.
Östberga station
Östberga station is a local railway stop serving the suburban area of Djursholm in the Stockholm metropolitan region of Sweden.
-
D.
Skogen station
Skogen station is a small metro stop on Oslo’s Holmenkollen Line (Line 1), serving the hillside residential area of Skogen in the Vestre Aker district.
-
E.
Högberga station
Högberga station is a local stop on the Lidingöbanan light rail line serving the Högberga area on Lidingö Island near Stockholm, Sweden.
- 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_69e0b4bf58c081908e52a4500e03ff83 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6af2133048190a6308074a3b3347e |
completed | April 20, 2026, 10:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a08cd56ad988190b2a44569b1e9e46b |
completed | May 16, 2026, 8:02 p.m. |
| NEDg | Description generation | batch_6a08d174278481909db394da2a7ff969 |
completed | May 16, 2026, 8:20 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a08d293523c8190aaa01c6c73c9afd5 |
completed | May 16, 2026, 8:24 p.m. |
Created at: April 16, 2026, 11:43 a.m.