Triple
T7471779
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oslo Metro Line 4 |
E176523
|
entity |
| Predicate | servesStation |
P839
|
FINISHED |
| Object |
Hasle station
Hasle station is a stop on the Oslo Metro system in Norway, serving the residential and commercial area of Hasle.
|
E669846
|
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: Hasle station | Statement: [Oslo Metro Line 4, servesStation, Hasle station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hasle station Context triple: [Oslo Metro Line 4, servesStation, Hasle station]
-
A.
Hokksund Station
Hokksund Station is a railway station in Hokksund, Norway, serving as a local and regional transport hub on the country’s rail network.
-
B.
Verdal Station
Verdal Station is a railway station in the town of Verdal in Trøndelag county, Norway, serving as a stop on the Nordland Line.
-
C.
Vegårshei Station
Vegårshei Station is a railway station in Vegårshei, Norway, serving as a local stop on the Sørlandet Line.
-
D.
Hynnekleiv Station
Hynnekleiv Station is a railway station serving the village of Hynnekleiv in the municipality of Froland in Agder county, Norway.
-
E.
Elverum Station
Elverum Station is a railway station in the town of Elverum in Innlandet county, Norway, serving as a regional transport hub on the Røros Line.
- 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: Hasle station Triple: [Oslo Metro Line 4, servesStation, Hasle station]
Generated description
Hasle station is a stop on the Oslo Metro system in Norway, serving the residential and commercial area of Hasle.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hasle station Target entity description: Hasle station is a stop on the Oslo Metro system in Norway, serving the residential and commercial area of Hasle.
-
A.
Hokksund Station
Hokksund Station is a railway station in Hokksund, Norway, serving as a local and regional transport hub on the country’s rail network.
-
B.
Verdal Station
Verdal Station is a railway station in the town of Verdal in Trøndelag county, Norway, serving as a stop on the Nordland Line.
-
C.
Vegårshei Station
Vegårshei Station is a railway station in Vegårshei, Norway, serving as a local stop on the Sørlandet Line.
-
D.
Hynnekleiv Station
Hynnekleiv Station is a railway station serving the village of Hynnekleiv in the municipality of Froland in Agder county, Norway.
-
E.
Elverum Station
Elverum Station is a railway station in the town of Elverum in Innlandet county, Norway, serving as a regional transport hub on the Røros Line.
- 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_69c69f223fd88190b4c69b95d7cbeeda |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f415b5cc81909e1e097c90f460b6 |
completed | March 27, 2026, 9:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c845f8b9a48190a21cac7fb98bf26d |
completed | March 28, 2026, 9:19 p.m. |
| NEDg | Description generation | batch_69c8478589248190b77df9a137bc67bf |
completed | March 28, 2026, 9:26 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c847d3ccd48190b818364fc34d9972 |
completed | March 28, 2026, 9:27 p.m. |
Created at: March 27, 2026, 3:41 p.m.