Triple
T7386808
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Suter |
E170401
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Heinz Suter
Heinz Suter is a Swiss former footballer known for his career in the Swiss domestic leagues during the 1970s and 1980s.
|
E681307
|
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: Heinz Suter | Statement: [Suter, hasNotableBearer, Heinz Suter]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Heinz Suter Context triple: [Suter, hasNotableBearer, Heinz Suter]
-
A.
Otmar Hasler
Otmar Hasler is a Liechtenstein politician who served as Prime Minister under Prince Hans-Adam II.
-
B.
Thomas Häßler
Thomas Häßler is a former German attacking midfielder renowned for his playmaking skills and key role in Germany’s 1990 World Cup and Euro 1996 triumphs.
-
C.
Klaus Tschütscher
Klaus Tschütscher is a Liechtenstein politician who served as the country's Prime Minister in the early 21st century.
-
D.
Heinz Schaller
Heinz Schaller was a German molecular biologist and entrepreneur best known for co-founding the biotechnology company Biogen.
-
E.
Martin Suter
Martin Suter is a Swiss author best known for his popular contemporary novels and crime fiction, including the successful "Business Class" stories and the Allmen detective series.
- 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: Heinz Suter Triple: [Suter, hasNotableBearer, Heinz Suter]
Generated description
Heinz Suter is a Swiss former footballer known for his career in the Swiss domestic leagues during the 1970s and 1980s.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Heinz Suter Target entity description: Heinz Suter is a Swiss former footballer known for his career in the Swiss domestic leagues during the 1970s and 1980s.
-
A.
Otmar Hasler
Otmar Hasler is a Liechtenstein politician who served as Prime Minister under Prince Hans-Adam II.
-
B.
Thomas Häßler
Thomas Häßler is a former German attacking midfielder renowned for his playmaking skills and key role in Germany’s 1990 World Cup and Euro 1996 triumphs.
-
C.
Klaus Tschütscher
Klaus Tschütscher is a Liechtenstein politician who served as the country's Prime Minister in the early 21st century.
-
D.
Heinz Schaller
Heinz Schaller was a German molecular biologist and entrepreneur best known for co-founding the biotechnology company Biogen.
-
E.
Martin Suter
Martin Suter is a Swiss author best known for his popular contemporary novels and crime fiction, including the successful "Business Class" stories and the Allmen detective series.
- 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_69c68a5e2c9081909e713ce866e0060a |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f1f2bac481908ac74069182a4ce4 |
completed | March 27, 2026, 9:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8a201e73081908cbe64f351e36f77 |
completed | March 29, 2026, 3:52 a.m. |
| NEDg | Description generation | batch_69c8a3a3cc2081909a5a2041cbdbe04f |
completed | March 29, 2026, 3:59 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c8a4257d9c8190a6b13bc9d5491476 |
completed | March 29, 2026, 4:01 a.m. |
Created at: March 27, 2026, 3:08 p.m.