Triple
T10428606
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flesberg |
E245849
|
entity |
| Predicate | administrativeCentre |
P1474
|
FINISHED |
| Object |
Lampeland
Lampeland is a small village in Buskerud, Norway, known as the main local hub of the rural Flesberg municipality.
|
E862702
|
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: Lampeland | Statement: [Flesberg, administrativeCentre, Lampeland]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lampeland Context triple: [Flesberg, administrativeCentre, Lampeland]
-
A.
Wallaceville
Wallaceville is a residential suburb located within the Hutt Valley region near Wellington, New Zealand.
-
B.
Baysville
Baysville is a small rural community in Ontario, Canada, known for its scenic lakeside setting and role as a cottage-country destination within the Muskoka region.
-
C.
Glen Haven
Glen Haven is a small community located within the Township of South Dundas in eastern Ontario, Canada.
-
D.
Parkeston
Parkeston is a village and port area in Essex, England, situated near Harwich and known historically for its railway and maritime connections.
-
E.
Brimley
Brimley is a surname most notably associated with American actor Wilford Brimley, known for his roles in film, television, and commercials.
- 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: Lampeland Triple: [Flesberg, administrativeCentre, Lampeland]
Generated description
Lampeland is a small village in Buskerud, Norway, known as the main local hub of the rural Flesberg municipality.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lampeland Target entity description: Lampeland is a small village in Buskerud, Norway, known as the main local hub of the rural Flesberg municipality.
-
A.
Wallaceville
Wallaceville is a residential suburb located within the Hutt Valley region near Wellington, New Zealand.
-
B.
Baysville
Baysville is a small rural community in Ontario, Canada, known for its scenic lakeside setting and role as a cottage-country destination within the Muskoka region.
-
C.
Glen Haven
Glen Haven is a small community located within the Township of South Dundas in eastern Ontario, Canada.
-
D.
Parkeston
Parkeston is a village and port area in Essex, England, situated near Harwich and known historically for its railway and maritime connections.
-
E.
Brimley
Brimley is a surname most notably associated with American actor Wilford Brimley, known for his roles in film, television, and commercials.
- 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_69d381bf3dc08190bf35a2643e4e8f22 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4ea4b4b5881908ae23f8efeea482b |
completed | April 7, 2026, 11:28 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d7fc2d54048190b25f4d168a75ad3a |
completed | April 9, 2026, 7:21 p.m. |
| NEDg | Description generation | batch_69d822d76f3481909f7c04be19414b14 |
completed | April 9, 2026, 10:06 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d85a00e7f48190bf87ce9d04acc750 |
completed | April 10, 2026, 2:01 a.m. |
Created at: April 6, 2026, 12:13 p.m.