Triple
T10377529
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MCH Group |
E244543
|
entity |
| Predicate | hasSubsidiary |
P254
|
FINISHED |
| Object |
MCH Messe Basel
MCH Messe Basel is a Swiss exhibition and event venue operator in Basel, known for hosting major international trade fairs and conferences.
|
E859765
|
NE FINISHED |
How this triple was built (4 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: MCH Messe Basel | Statement: [MCH Group, hasSubsidiary, MCH Messe Basel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MCH Messe Basel Context triple: [MCH Group, hasSubsidiary, MCH Messe Basel]
-
A.
Messe
Messe is a Nuremberg U-Bahn station serving the city’s exhibition and trade fair grounds.
-
B.
Art Basel
Art Basel is a leading international art fair brand that stages major contemporary and modern art shows in cities such as Basel, Miami Beach, and Hong Kong.
-
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 Berlin
Messe Berlin is a major exhibition and trade fair center in Berlin, Germany, hosting international trade shows, conferences, and large-scale events.
-
E.
Koelnmesse
Koelnmesse is a major international trade fair and exhibition company based in Cologne, Germany, known for organizing prominent events across various industries.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: MCH Messe Basel Triple: [MCH Group, hasSubsidiary, MCH Messe Basel]
Generated description
MCH Messe Basel is a Swiss exhibition and event venue operator in Basel, known for hosting major international trade fairs and conferences.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: MCH Messe Basel Target entity description: MCH Messe Basel is a Swiss exhibition and event venue operator in Basel, known for hosting major international trade fairs and conferences.
-
A.
Messe
Messe is a Nuremberg U-Bahn station serving the city’s exhibition and trade fair grounds.
-
B.
Art Basel
Art Basel is a leading international art fair brand that stages major contemporary and modern art shows in cities such as Basel, Miami Beach, and Hong Kong.
-
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 Berlin
Messe Berlin is a major exhibition and trade fair center in Berlin, Germany, hosting international trade shows, conferences, and large-scale events.
-
E.
Koelnmesse
Koelnmesse is a major international trade fair and exhibition company based in Cologne, Germany, known for organizing prominent events across various industries.
- F. None of above. chosen
Provenance (5 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_69d381b3e328819094b23b8edcd29b5a |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e98f312481909f7276fc3762d7bc |
completed | April 7, 2026, 11:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d7957e52108190a8d262b30a7d2780 |
completed | April 9, 2026, 12:03 p.m. |
| NEDg | Description generation | batch_69d798e3dba08190911fc9fec5d2c8e2 |
completed | April 9, 2026, 12:17 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d79a6086fc8190ab8454a216dfda8c |
completed | April 9, 2026, 12:24 p.m. |
Created at: April 6, 2026, 12:03 p.m.