Triple
T13401080
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oslo Spektrum |
E319827
|
entity |
| Predicate | operator |
P179
|
FINISHED |
| Object | Norges Varemesse |
E1039093
|
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: Norges Varemesse | Statement: [Oslo Spektrum, operator, Norges Varemesse]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Norges Varemesse Context triple: [Oslo Spektrum, operator, Norges Varemesse]
-
A.
Norges Varemesse
chosen
Norges Varemesse is a major Norwegian exhibition and convention company that operates large event and trade fair venues, including the Oslo Spektrum arena.
-
B.
Frankfurt Trade Fair
The Frankfurt Trade Fair is one of the world’s oldest and largest international trade fair venues, renowned for hosting major global exhibitions and industry events in Frankfurt, Germany.
-
C.
Koelnmesse
Koelnmesse is a major international trade fair and exhibition company based in Cologne, Germany, known for organizing prominent events across various industries.
-
D.
Nürnberg Messe
Nürnberg Messe is one of Germany’s largest international trade fair and exhibition centers, hosting numerous global industry events and conferences in Nuremberg.
-
E.
Messe
Messe is a Nuremberg U-Bahn station serving the city’s exhibition and trade fair grounds.
- 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_69d806b943cc8190b6af624d385d7e12 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbae4982e0819087a9fcb2fa88541f |
completed | April 12, 2026, 2:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f73983b8f08190bf4d1a64c0beab97 |
completed | May 3, 2026, 12:03 p.m. |
Created at: April 9, 2026, 9:34 p.m.