Triple
T22749237
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Melhus |
E562643
|
entity |
| Predicate | hasRailwayStation |
P918
|
FINISHED |
| Object |
Ler Station
Ler Station is a local railway station serving the village of Ler in Melhus municipality in Trøndelag county, Norway.
|
E1551435
|
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: Ler Station | Statement: [Melhus, hasRailwayStation, Ler Station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ler Station Context triple: [Melhus, hasRailwayStation, Ler Station]
-
A.
Leer railway station
Leer railway station is a regional rail hub in the town of Leer in Lower Saxony, Germany, serving passenger and local train services.
-
B.
Vinstra Station
Vinstra Station is a railway station in the town of Vinstra in Innlandet county, Norway, serving as a stop on the Dovre Line.
-
C.
Teine Station
Teine Station is a key railway station in Sapporo, Hokkaido, Japan, serving as an important hub for local and regional train services.
-
D.
Tretten Station
Tretten Station is a railway station serving the village of Tretten in Øyer municipality, Innlandet county, Norway.
-
E.
Ryers station
Ryers station is a commuter rail stop in Philadelphia, Pennsylvania, served by SEPTA's Fox Chase 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: Ler Station Triple: [Melhus, hasRailwayStation, Ler Station]
Generated description
Ler Station is a local railway station serving the village of Ler in Melhus municipality in Trøndelag county, Norway.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ler Station Target entity description: Ler Station is a local railway station serving the village of Ler in Melhus municipality in Trøndelag county, Norway.
-
A.
Leer railway station
Leer railway station is a regional rail hub in the town of Leer in Lower Saxony, Germany, serving passenger and local train services.
-
B.
Vinstra Station
Vinstra Station is a railway station in the town of Vinstra in Innlandet county, Norway, serving as a stop on the Dovre Line.
-
C.
Teine Station
Teine Station is a key railway station in Sapporo, Hokkaido, Japan, serving as an important hub for local and regional train services.
-
D.
Tretten Station
Tretten Station is a railway station serving the village of Tretten in Øyer municipality, Innlandet county, Norway.
-
E.
Ryers station
Ryers station is a commuter rail stop in Philadelphia, Pennsylvania, served by SEPTA's Fox Chase 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_69e24551ec7881909a9c924dbea155f6 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f179b822988190b5368ac1f4e1d70a |
completed | April 29, 2026, 3:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0b8fd5c05c819091c2871dc9e4e9ca |
completed | May 18, 2026, 10:16 p.m. |
| NEDg | Description generation | batch_6a0b90addad481909a69601ed3d50622 |
completed | May 18, 2026, 10:20 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0b9118ebd48190adf5e7fd47408dc7 |
completed | May 18, 2026, 10:22 p.m. |
Created at: April 17, 2026, 3:24 p.m.