Triple
T4212029
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Düsseldorfer EG |
E93923
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object |
DEG
DEG is a professional ice hockey club based in Düsseldorf, Germany, competing in the country’s top-tier league and known for its rich history and multiple championship titles.
|
E421966
|
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: DEG | Statement: [Düsseldorfer EG, shortName, DEG]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DEG Context triple: [Düsseldorfer EG, shortName, DEG]
-
A.
DEB
DEB is the abbreviation for the Deutscher Eishockey-Bund, the governing body for ice hockey in Germany.
-
B.
DHE
DHE is the Massachusetts state agency responsible for coordinating and overseeing public higher education institutions and policies.
-
C.
DELAG
DELAG was the world’s first airline to use rigid airships for passenger transport, pioneering commercial air travel in the early 20th century.
-
D.
DESE
DESE is the state agency responsible for overseeing public elementary and secondary education in Massachusetts, including standards, accountability, and school support.
-
E.
DEFR
DEFR is the commonly used abbreviation for the Swiss Federal Department of Economic Affairs, Education and Research, which oversees national policy in those three areas.
- 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: DEG Triple: [Düsseldorfer EG, shortName, DEG]
Generated description
DEG is a professional ice hockey club based in Düsseldorf, Germany, competing in the country’s top-tier league and known for its rich history and multiple championship titles.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: DEG Target entity description: DEG is a professional ice hockey club based in Düsseldorf, Germany, competing in the country’s top-tier league and known for its rich history and multiple championship titles.
-
A.
DEB
DEB is the abbreviation for the Deutscher Eishockey-Bund, the governing body for ice hockey in Germany.
-
B.
DHE
DHE is the Massachusetts state agency responsible for coordinating and overseeing public higher education institutions and policies.
-
C.
DELAG
DELAG was the world’s first airline to use rigid airships for passenger transport, pioneering commercial air travel in the early 20th century.
-
D.
DESE
DESE is the state agency responsible for overseeing public elementary and secondary education in Massachusetts, including standards, accountability, and school support.
-
E.
DEFR
DEFR is the commonly used abbreviation for the Swiss Federal Department of Economic Affairs, Education and Research, which oversees national policy in those three areas.
- 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_69b3451743608190808f41d17ccf2650 |
completed | March 12, 2026, 10:58 p.m. |
| NER | Named-entity recognition | batch_69b3481219a08190b17bf3b414bd7d4a |
completed | March 12, 2026, 11:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b59631e2cc8190b1d125b82a81593e |
completed | March 14, 2026, 5:09 p.m. |
| NEDg | Description generation | batch_69b5970db8b48190b952d0fa08234f09 |
completed | March 14, 2026, 5:12 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b59788ef308190a34c2f23f22a7e4d |
completed | March 14, 2026, 5:14 p.m. |
Created at: March 12, 2026, 11:04 p.m.