Triple
T18597544
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Midttrafik |
E454531
|
entity |
| Predicate | operatesIn |
P82
|
FINISHED |
| Object | Randers |
—
|
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: Randers | Statement: [Midttrafik, operatesIn, Randers]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Randers Context triple: [Midttrafik, operatesIn, Randers]
-
A.
Randers
chosen
Randers is a historic market town and one of the largest cities in eastern Jutland, Denmark, known for its old town center and location along the Gudenå River.
-
B.
Kolding
Kolding is a historic Danish city in Southern Jutland known for Koldinghus Castle, its fjord-side location, and its role as a regional cultural and educational center.
-
C.
Horsens
Horsens is a city in eastern Jutland, Denmark, known historically as a market and industrial town and as the birthplace of explorer Vitus Bering.
-
D.
Herning
Herning is a Danish city in the Central Jutland region known for its trade fairs, conference facilities, and vibrant cultural and sports events.
-
E.
Aalborg
Aalborg is a major city in northern Denmark known for its historic architecture, vibrant cultural life, and role as a regional economic and educational center.
- 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.