Triple
T20642987
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deutsche Messe AG |
E507276
|
entity |
| Predicate | hasNotableEvent |
P259
|
FINISHED |
| Object | Agritechnica |
—
|
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: Agritechnica | Statement: [Deutsche Messe AG, hasNotableEvent, Agritechnica]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Agritechnica Context triple: [Deutsche Messe AG, hasNotableEvent, Agritechnica]
-
A.
Agritechnica
chosen
Agritechnica is a leading international trade fair for agricultural machinery and technology held in Germany.
-
B.
Hannover Messe
Hannover Messe is one of the world’s largest and most influential industrial technology trade fairs, held annually in Hanover, Germany.
-
C.
National Farm Machinery Show
The National Farm Machinery Show is a major annual agricultural trade show in the United States showcasing the latest farm equipment, technology, and services to farmers and industry professionals.
-
D.
Berliner Messe
Berliner Messe is a minimalist sacred choral composition by Estonian composer Arvo Pärt, written in his signature tintinnabuli style for the Latin Mass.
-
E.
Fruit Logistica
Fruit Logistica is a leading international trade fair for the global fresh fruit and vegetable industry, showcasing products, innovations, and services across the entire supply chain.
- 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_69e0b4be702c8190a3d2410a881d310a |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6af1c51f48190abba54a5aace9fc8 |
completed | April 20, 2026, 10:56 p.m. |
Created at: April 16, 2026, 11:43 a.m.