Triple
T13448364
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sarek National Park |
E320542
|
entity |
| Predicate | accessPoint |
P1985
|
FINISHED |
| Object |
Saltoluokta
Saltoluokta is a well-known mountain station and gateway in Swedish Lapland that serves as a popular starting point for hiking and outdoor adventures in the surrounding national parks.
|
E1041131
|
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: Saltoluokta | Statement: [Sarek National Park, accessPoint, Saltoluokta]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Saltoluokta Context triple: [Sarek National Park, accessPoint, Saltoluokta]
-
A.
Salamansa
Salamansa is a coastal village on the island of São Vicente in Cape Verde, known for its fishing community and sandy beach.
-
B.
Saluan
Saluan is an Austronesian language spoken by the Saluan people primarily in Central Sulawesi, Indonesia.
-
C.
Sivaraksa
Sivaraksa is the surname of Sulak Sivaraksa, a prominent Thai social activist, intellectual, and proponent of engaged Buddhism.
-
D.
Salekasa
Salekasa is a town in the Gondia district of Maharashtra, India.
-
E.
Liotta
Liotta is an Italian-origin surname most famously associated with American actor Ray Liotta, known for his roles in films like "Goodfellas."
- 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: Saltoluokta Triple: [Sarek National Park, accessPoint, Saltoluokta]
Generated description
Saltoluokta is a well-known mountain station and gateway in Swedish Lapland that serves as a popular starting point for hiking and outdoor adventures in the surrounding national parks.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Saltoluokta Target entity description: Saltoluokta is a well-known mountain station and gateway in Swedish Lapland that serves as a popular starting point for hiking and outdoor adventures in the surrounding national parks.
-
A.
Salamansa
Salamansa is a coastal village on the island of São Vicente in Cape Verde, known for its fishing community and sandy beach.
-
B.
Saluan
Saluan is an Austronesian language spoken by the Saluan people primarily in Central Sulawesi, Indonesia.
-
C.
Sivaraksa
Sivaraksa is the surname of Sulak Sivaraksa, a prominent Thai social activist, intellectual, and proponent of engaged Buddhism.
-
D.
Salekasa
Salekasa is a town in the Gondia district of Maharashtra, India.
-
E.
Liotta
Liotta is an Italian-origin surname most famously associated with American actor Ray Liotta, known for his roles in films like "Goodfellas."
- 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_69d80761e6cc8190a90c844589998ecc |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbaef758b08190b9aa5ec7082cd417 |
completed | April 12, 2026, 2:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f73998221c8190a2d8982a3da28ec9 |
completed | May 3, 2026, 12:03 p.m. |
| NEDg | Description generation | batch_69f73a598c6c81908420b00b665e3b08 |
completed | May 3, 2026, 12:06 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f73e0e598c8190b030a45e658a5055 |
completed | May 3, 2026, 12:22 p.m. |
Created at: April 9, 2026, 9:41 p.m.