Triple
T5263680
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CeBIT |
E118886
|
entity |
| Predicate | separatedFrom |
P243
|
FINISHED |
| Object | Hannover Messe |
E118885
|
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: Hannover Messe | Statement: [CeBIT, separatedFrom, Hannover Messe]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hannover Messe Context triple: [CeBIT, separatedFrom, Hannover Messe]
-
A.
Hannover Messe
chosen
Hannover Messe is one of the world’s largest and most influential industrial technology trade fairs, held annually in Hanover, Germany.
-
B.
Messe Berlin
Messe Berlin is a major exhibition and trade fair center in Berlin, Germany, hosting international trade shows, conferences, and large-scale events.
-
C.
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.
-
D.
Messe Düsseldorf
Messe Düsseldorf is a major international trade fair and exhibition center in Düsseldorf, Germany, hosting numerous global industry events and conventions.
-
E.
Leipzig Trade Fair (Leipziger Messe)
Leipzig Trade Fair (Leipziger Messe) is one of the world’s oldest and most prominent trade fair organizations, hosting major international exhibitions and conferences in Leipzig, Germany.
- 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_69bd446a42c88190b7ecbef006561d55 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7bd2eff4819087420e30c140e6f6 |
completed | March 20, 2026, 4:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf06c71d308190a42a2da51b4cf93e |
completed | March 21, 2026, 8:59 p.m. |
Created at: March 20, 2026, 1:51 p.m.