Triple
T18908981
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Czech Cup |
E462546
|
entity |
| Predicate | sponsor |
P67
|
FINISHED |
| Object |
MOL Group
MOL Group is a Hungarian multinational oil and gas company that operates across Central and Eastern Europe in exploration, production, refining, and retail.
|
E1348456
|
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: MOL Group | Statement: [Czech Cup, sponsor, MOL Group]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MOL Group Context triple: [Czech Cup, sponsor, MOL Group]
-
A.
MOL Global
MOL Global was a Malaysian online payment solutions provider best known for acquiring the once-popular social networking site Friendster.
-
B.
MOL
MOL is the vehicle registration code used on license plates for the Märkisch-Oderland district in the German state of Brandenburg.
-
C.
MOL
MOL is the IATA airport code for Molde Airport, Årø, which serves the town of Molde in Norway.
-
D.
MOL
MOL is the abbreviated name of Taiwan’s Ministry of Labor, the central government agency responsible for labor policy, employment affairs, and workers’ rights.
-
E.
Uniper
Uniper is a German energy company focused on power generation and global energy trading, formed from the conventional energy business spun off from E.ON.
- 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: MOL Group Triple: [Czech Cup, sponsor, MOL Group]
Generated description
MOL Group is a Hungarian multinational oil and gas company that operates across Central and Eastern Europe in exploration, production, refining, and retail.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: MOL Group Target entity description: MOL Group is a Hungarian multinational oil and gas company that operates across Central and Eastern Europe in exploration, production, refining, and retail.
-
A.
MOL Global
MOL Global was a Malaysian online payment solutions provider best known for acquiring the once-popular social networking site Friendster.
-
B.
MOL
MOL is the vehicle registration code used on license plates for the Märkisch-Oderland district in the German state of Brandenburg.
-
C.
MOL
MOL is the IATA airport code for Molde Airport, Årø, which serves the town of Molde in Norway.
-
D.
MOL
MOL is the abbreviated name of Taiwan’s Ministry of Labor, the central government agency responsible for labor policy, employment affairs, and workers’ rights.
-
E.
Uniper
Uniper is a German energy company focused on power generation and global energy trading, formed from the conventional energy business spun off from E.ON.
- 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_69d8dcfd05bc819088903cca13cc2846 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5c52eed1881908929dace845ae008 |
completed | April 20, 2026, 6:18 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0582c196888190aa49b219aedb06e2 |
completed | May 14, 2026, 8:07 a.m. |
| NEDg | Description generation | batch_6a05890d8a1c819081ad3d12ea9c4d5e |
completed | May 14, 2026, 8:34 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0589a3c0c08190be4b6dd6e9a56fdb |
completed | May 14, 2026, 8:36 a.m. |
Created at: April 10, 2026, 11:58 a.m.