Triple
T5263661
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CeBIT |
E118886
|
entity |
| Predicate | organizer |
P123
|
FINISHED |
| Object | Deutsche Messe AG |
E507276
|
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: Deutsche Messe AG | Statement: [CeBIT, organizer, Deutsche Messe AG]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Deutsche Messe AG Context triple: [CeBIT, organizer, Deutsche Messe AG]
-
A.
Deutsche Messe AG
chosen
Deutsche Messe AG is a major German trade fair company best known for staging large international industrial and technology exhibitions, including the Hannover Messe.
-
B.
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.
-
C.
S7 Group
S7 Group is a Russian aviation holding company best known for owning and operating S7 Airlines and related air transport businesses.
-
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.
Robert Bosch Stiftung
Robert Bosch Stiftung is a major German charitable foundation that supports initiatives in areas such as education, health, science, and international understanding.
- 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.