Triple
T2206930
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Østfold Line |
E50820
|
entity |
| Predicate | connectsCity |
P4245
|
FINISHED |
| Object |
Ski
Ski is a town in Viken county, Norway, serving as a regional commercial and transport hub southeast of Oslo.
|
E245864
|
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: Ski | Statement: [Østfold Line, connectsCity, Ski]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ski Context triple: [Østfold Line, connectsCity, Ski]
-
A.
Nordic skiing
Nordic skiing is a category of winter sports that involves traveling over snow on skis using the skier’s own locomotion, including disciplines like cross-country skiing and ski jumping.
-
B.
Ski Bowl
Ski Bowl is a popular ski and snowboard resort located on the slopes of Mount Hood in Oregon, known for its extensive night skiing and varied terrain.
-
C.
Snowpark
Snowpark is a developer framework from Snowflake that lets data engineers and data scientists write data pipelines and applications in languages like Python, Java, and Scala directly within the Snowflake data platform.
-
D.
The Slopes
The Slopes is a historic landscaped park in Buxton, Derbyshire, known for its terraced walks, ornamental gardens, and views over the town’s spa architecture.
-
E.
WATERSKI
WATERSKI is the former radio callsign used by Trans States Airlines for air traffic control communications.
- 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: Ski Triple: [Østfold Line, connectsCity, Ski]
Generated description
Ski is a town in Viken county, Norway, serving as a regional commercial and transport hub southeast of Oslo.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ski Target entity description: Ski is a town in Viken county, Norway, serving as a regional commercial and transport hub southeast of Oslo.
-
A.
Nordic skiing
Nordic skiing is a category of winter sports that involves traveling over snow on skis using the skier’s own locomotion, including disciplines like cross-country skiing and ski jumping.
-
B.
Ski Bowl
Ski Bowl is a popular ski and snowboard resort located on the slopes of Mount Hood in Oregon, known for its extensive night skiing and varied terrain.
-
C.
Snowpark
Snowpark is a developer framework from Snowflake that lets data engineers and data scientists write data pipelines and applications in languages like Python, Java, and Scala directly within the Snowflake data platform.
-
D.
The Slopes
The Slopes is a historic landscaped park in Buxton, Derbyshire, known for its terraced walks, ornamental gardens, and views over the town’s spa architecture.
-
E.
WATERSKI
WATERSKI is the former radio callsign used by Trans States Airlines for air traffic control communications.
- 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_69a88b06709c8190978fb2418470d1b6 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abbfcbb83081908d5b2f1603c7b4d2 |
completed | March 7, 2026, 6:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae654b89b081908f8c8b9bfc0b6579 |
completed | March 9, 2026, 6:14 a.m. |
| NEDg | Description generation | batch_69ae667dede88190b3d1f8bb8866e19e |
completed | March 9, 2026, 6:19 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae66f12c648190a146de7b2bfdb541 |
completed | March 9, 2026, 6:21 a.m. |
Created at: March 4, 2026, 7:46 p.m.