Triple
T18597557
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Midttrafik |
E454531
|
entity |
| Predicate | operatesIn |
P82
|
FINISHED |
| Object | Struer |
—
|
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: Struer | Statement: [Midttrafik, operatesIn, Struer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Struer Context triple: [Midttrafik, operatesIn, Struer]
-
A.
Struer
chosen
Struer is a Danish town in the Central Denmark Region known for its location on the Limfjord and as the historic home of the audio company Bang & Olufsen.
-
B.
Magura
Magura is a town and district headquarters in southwestern Bangladesh known for its agricultural surroundings and location within the Khulna Division.
-
C.
Magura
Magura is a mountain peak in the Kysucké Beskydy range of northern Slovakia, known for its forested slopes and scenic hiking routes.
-
D.
Skeid
Skeid is a Norwegian sports club best known for its football team and local rivalry with Lyn in Oslo.
-
E.
Menzlin
Menzlin is a small locality in northeastern Germany, historically part of Pomerania.
- 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.