Triple
T16724553
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | WEOG |
E406435
|
entity |
| Predicate | hasMember |
P10
|
FINISHED |
| Object | Denmark |
E5474
|
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: Denmark | Statement: [WEOG, hasMember, Denmark]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Denmark Context triple: [WEOG, hasMember, Denmark]
-
A.
Denmark
chosen
Denmark is a Nordic country in Northern Europe known for its high standard of living, strong welfare state, and role as a founding member of NATO and the United Nations.
-
B.
Dania
Dania was the original name of the South Florida city now known as Dania Beach, historically recognized as one of the region’s earliest incorporated communities.
-
C.
Daens
Daens is a 1992 Belgian historical drama film about a Catholic priest who fights social injustice and exploitation of workers in late 19th-century Belgium.
-
D.
Sweden and Denmark
Sweden and Denmark are neighboring Scandinavian countries in Northern Europe, separated by the Øresund Strait and closely linked through extensive cultural, economic, and transport connections.
-
E.
Norway
Norway is a Nordic country in Northern Europe known for its high standard of living, extensive welfare state, and dramatic natural landscapes of fjords, mountains, and coastline.
- 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_69d8838f242881908abd8bc138795886 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e38746c8fc81908b9fade26f37be11 |
completed | April 18, 2026, 1:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00b27fbce0819084852678798f264e |
completed | May 10, 2026, 4:29 p.m. |
Created at: April 10, 2026, 5:20 a.m.