Triple
T3496495
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Øresund Region |
E73863
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Region Zealand |
E215864
|
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: Region Zealand | Statement: [Øresund Region, hasPart, Region Zealand]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Region Zealand Context triple: [Øresund Region, hasPart, Region Zealand]
-
A.
Region Zealand
chosen
Region Zealand is an administrative region in eastern Denmark that encompasses the southern and western parts of the island of Zealand and nearby islands.
-
B.
Zealand
Zealand is the largest and most populous island of Denmark, home to the capital city Copenhagen and a central hub of the country’s cultural and economic life.
-
C.
Zealand Region
Zealand Region is an administrative region of Denmark that encompasses the island of Zealand (excluding the Copenhagen area) and nearby islands, with responsibilities for healthcare and regional development.
-
D.
Vestland
Vestland is a county in western Norway known for its dramatic fjords, coastal landscapes, and the city of Bergen.
-
E.
Seeland region
The Seeland region is an area in western Switzerland known for its lakes, fertile plains, and intensive agriculture, particularly vegetable farming.
- 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_69ad85cdb6e48190a335d412b9194ed8 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbbd16c0081908f13535f459618d1 |
completed | March 8, 2026, 6:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b373cce4008190beb010b171bc4940 |
completed | March 13, 2026, 2:17 a.m. |
Created at: March 8, 2026, 3:18 p.m.