Triple
T9182637
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lolland |
E220370
|
entity |
| Predicate | largestTown |
P235
|
FINISHED |
| Object |
Nakskov
Nakskov is a historic port town in southern Denmark located on the island of Lolland, known for its maritime industry and coastal setting.
|
E823073
|
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: Nakskov | Statement: [Lolland, largestTown, Nakskov]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nakskov Context triple: [Lolland, largestTown, Nakskov]
-
A.
Vadsø
Vadsø is a small coastal town and administrative center in Finnmark, known for its Arctic location on the Varanger Peninsula and its role as a hub of Sami and Kven culture in Northern Norway.
-
B.
Oksbøl
Oksbøl is a town in southwestern Jutland, Denmark, known for its military training areas and historical role as a garrison location.
-
C.
Hellebæk
Hellebæk is a coastal town in northeastern Zealand, Denmark, known for its scenic setting near Helsingør and its historic industrial and residential architecture.
-
D.
Næstved
Næstved is a historic market town and commercial center in southern Denmark, located on the island of Zealand.
-
E.
Vækerø
Vækerø is a residential and commercial area in Oslo, Norway, located along the western waterfront and known for its mix of housing, offices, and green spaces.
- 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: Nakskov Triple: [Lolland, largestTown, Nakskov]
Generated description
Nakskov is a historic port town in southern Denmark located on the island of Lolland, known for its maritime industry and coastal setting.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nakskov Target entity description: Nakskov is a historic port town in southern Denmark located on the island of Lolland, known for its maritime industry and coastal setting.
-
A.
Vadsø
Vadsø is a small coastal town and administrative center in Finnmark, known for its Arctic location on the Varanger Peninsula and its role as a hub of Sami and Kven culture in Northern Norway.
-
B.
Oksbøl
Oksbøl is a town in southwestern Jutland, Denmark, known for its military training areas and historical role as a garrison location.
-
C.
Hellebæk
Hellebæk is a coastal town in northeastern Zealand, Denmark, known for its scenic setting near Helsingør and its historic industrial and residential architecture.
-
D.
Næstved
Næstved is a historic market town and commercial center in southern Denmark, located on the island of Zealand.
-
E.
Vækerø
Vækerø is a residential and commercial area in Oslo, Norway, located along the western waterfront and known for its mix of housing, offices, and green spaces.
- 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_69ca83e589948190ac9907819db11ddf |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccc2553e548190898434aeda517407 |
completed | April 1, 2026, 6:59 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1cc2ca7a081908f597e9a58920d6e |
completed | April 5, 2026, 2:42 a.m. |
| NEDg | Description generation | batch_69d1ccb043008190a3af47b234520891 |
completed | April 5, 2026, 2:45 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d1cd04694881909ab19cb4c11fbd20 |
completed | April 5, 2026, 2:46 a.m. |
Created at: March 30, 2026, 7:23 p.m.