Triple
T10892051
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ESV Kaufbeuren |
E257201
|
entity |
| Predicate | notablePlayerDeveloped |
P9670
|
FINISHED |
| Object |
Stefan Vogl
Stefan Vogl is an ice hockey player known for emerging from the development system of the German club ESV Kaufbeuren.
|
E901853
|
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: Stefan Vogl | Statement: [ESV Kaufbeuren, notablePlayerDeveloped, Stefan Vogl]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stefan Vogl Context triple: [ESV Kaufbeuren, notablePlayerDeveloped, Stefan Vogl]
-
A.
Stefan Grube
Stefan Grube is a film editor best known for his work on the thriller "10 Cloverfield Lane."
-
B.
Stefan Grube
Stefan Grube is an editor known for his work on the film "Tully."
-
C.
Ralf Wengenmayr
Ralf Wengenmayr is a German film composer known for scoring a variety of feature films and international productions.
-
D.
Markus Sattler
Markus Sattler is a German software engineer and entrepreneur best known as a co-founder and former CTO of the email marketing platform Mailjet.
-
E.
Andreas Huber
Andreas Huber is a relatively common German-speaking personal name shared by multiple individuals across fields such as sports, engineering, and the arts.
- 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: Stefan Vogl Triple: [ESV Kaufbeuren, notablePlayerDeveloped, Stefan Vogl]
Generated description
Stefan Vogl is an ice hockey player known for emerging from the development system of the German club ESV Kaufbeuren.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Stefan Vogl Target entity description: Stefan Vogl is an ice hockey player known for emerging from the development system of the German club ESV Kaufbeuren.
-
A.
Stefan Grube
Stefan Grube is a film editor best known for his work on the thriller "10 Cloverfield Lane."
-
B.
Stefan Grube
Stefan Grube is an editor known for his work on the film "Tully."
-
C.
Ralf Wengenmayr
Ralf Wengenmayr is a German film composer known for scoring a variety of feature films and international productions.
-
D.
Markus Sattler
Markus Sattler is a German software engineer and entrepreneur best known as a co-founder and former CTO of the email marketing platform Mailjet.
-
E.
Andreas Huber
Andreas Huber is a relatively common German-speaking personal name shared by multiple individuals across fields such as sports, engineering, and the arts.
- 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_69d6aa8550c8819095508a2ed9acf3db |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d75206354881908b148f2df3938513 |
completed | April 9, 2026, 7:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e3a92e09648190ab39053521211743 |
completed | April 18, 2026, 3:54 p.m. |
| NEDg | Description generation | batch_69e3abe492388190a2f5752f6bad1220 |
completed | April 18, 2026, 4:05 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69e3b1efe4a88190884eb5186954cf39 |
completed | April 18, 2026, 4:31 p.m. |
Created at: April 8, 2026, 9:21 p.m.