Triple
T18597546
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Midttrafik |
E454531
|
entity |
| Predicate | operatesIn |
P82
|
FINISHED |
| Object | Viborg |
—
|
NE NERFINISHED |
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: Viborg | Statement: [Midttrafik, operatesIn, Viborg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Viborg Context triple: [Midttrafik, operatesIn, Viborg]
-
A.
Viborg
chosen
Viborg is one of Denmark’s oldest cities, historically significant as a medieval political and religious center on the Jutland peninsula.
-
B.
Viborg
Viborg is the Swedish name for the historic Karelian city of Vyborg, located near the Finnish border on the Gulf of Finland.
-
C.
Vordingborg
Vordingborg is a historic coastal town in southern Denmark known for the ruins of Vordingborg Castle and its prominent Goose Tower.
-
D.
Fredericia
Fredericia is a Danish coastal town in Jutland known for its historic 17th-century fortress and well-preserved ramparts.
-
E.
Esbjerg
Esbjerg is a major Danish port city on the North Sea, known for its offshore oil and wind industry, maritime heritage, and role as a regional economic center in western Jutland.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8d38ae7e081908a98df1251842402 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5474d934481909b4afd5ef9031c73 |
completed | April 19, 2026, 9:21 p.m. |
Created at: April 10, 2026, 11:44 a.m.