Triple
T7587718
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ovanåker Municipality |
E179657
|
entity |
| Predicate | seat |
P75
|
FINISHED |
| Object |
Edsbyn
Edsbyn is a small town in Gävleborg County, Sweden, known for its bandy team and role as a local industrial and service center.
|
E675673
|
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: Edsbyn | Statement: [Ovanåker Municipality, seat, Edsbyn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Edsbyn Context triple: [Ovanåker Municipality, seat, Edsbyn]
-
A.
Eidskog
Eidskog is a rural municipality in Innlandet county, Norway, known for its forests, lakes, and location along the Swedish border.
-
B.
Lebesby
Lebesby is a sparsely populated coastal municipality in Troms og Finnmark county in northern Norway, known for its Arctic landscapes, fishing communities, and proximity to the Barents Sea.
-
C.
Nesbyen
Nesbyen is a small town and municipality in southeastern Norway known for its inland valley setting, historic wooden buildings, and notably warm summer temperatures.
-
D.
Nannfeldt
Nannfeldt was a mycologist and taxonomist known for his influential work on the classification and nomenclature of fungi, particularly within the Ascomycota.
-
E.
Mörby
Mörby is a locality in the Stockholm area of Sweden served by a station on the Roslagsbanan narrow-gauge railway 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: Edsbyn Triple: [Ovanåker Municipality, seat, Edsbyn]
Generated description
Edsbyn is a small town in Gävleborg County, Sweden, known for its bandy team and role as a local industrial and service center.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Edsbyn Target entity description: Edsbyn is a small town in Gävleborg County, Sweden, known for its bandy team and role as a local industrial and service center.
-
A.
Eidskog
Eidskog is a rural municipality in Innlandet county, Norway, known for its forests, lakes, and location along the Swedish border.
-
B.
Lebesby
Lebesby is a sparsely populated coastal municipality in Troms og Finnmark county in northern Norway, known for its Arctic landscapes, fishing communities, and proximity to the Barents Sea.
-
C.
Nesbyen
Nesbyen is a small town and municipality in southeastern Norway known for its inland valley setting, historic wooden buildings, and notably warm summer temperatures.
-
D.
Nannfeldt
Nannfeldt was a mycologist and taxonomist known for his influential work on the classification and nomenclature of fungi, particularly within the Ascomycota.
-
E.
Mörby
Mörby is a locality in the Stockholm area of Sweden served by a station on the Roslagsbanan narrow-gauge railway 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_69c69f335248819093c1006f30513708 |
completed | March 27, 2026, 3:16 p.m. |
| NER | Named-entity recognition | batch_69c6f99875908190b09584cf13ea1e08 |
completed | March 27, 2026, 9:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c86186ce4481908e528c57cdd07d2d |
completed | March 28, 2026, 11:17 p.m. |
| NEDg | Description generation | batch_69c86223bfec8190b47f840e39c9a51a |
completed | March 28, 2026, 11:20 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c862b8f3688190b0abc00458f70d7e |
completed | March 28, 2026, 11:22 p.m. |
Created at: March 27, 2026, 3:52 p.m.