Triple
T4581764
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jutland |
E101870
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | North Jutlandic Island |
E175967
|
NE FINISHED |
How this triple was built (2 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: North Jutlandic Island | Statement: [Jutland, hasPart, North Jutlandic Island]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: North Jutlandic Island Context triple: [Jutland, hasPart, North Jutlandic Island]
-
A.
North Jutlandic Island
chosen
North Jutlandic Island is a large island in northern Denmark separated from the rest of Jutland by the Limfjord and known for its coastal landscapes and tourism.
-
B.
Langeland
Langeland is a Danish island in the South Funen Archipelago, known for its rural landscapes, coastal scenery, and historical villages.
-
C.
Bornholm
Bornholm is a Danish island known for its rocky coastline, medieval ruins, and picturesque fishing villages in the Baltic Sea.
-
D.
Lolland
Lolland is a large, predominantly agricultural island in southeastern Denmark known for its flat landscape and sugar beet production.
-
E.
Møn
Møn is a Danish island in the Baltic Sea known for its dramatic white chalk cliffs, scenic landscapes, and rich prehistoric and cultural heritage.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69bd43d4ce208190b53158c882b222e3 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd590116e88190b8495b2a78cf3fb6 |
completed | March 20, 2026, 2:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bde09015c48190b4f992f3f95023cf |
completed | March 21, 2026, 12:04 a.m. |
Created at: March 20, 2026, 1:10 p.m.