Triple

T9751514
Position Surface form Disambiguated ID Type / Status
Subject Groth E236451 entity
Predicate hasNotableBearer P458 FINISHED
Object Steffen Groth
Steffen Groth is a German actor and director known for his roles in television series and films.
E818074 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: Steffen Groth | Statement: [Groth, hasNotableBearer, Steffen Groth]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Steffen Groth
Context triple: [Groth, hasNotableBearer, Steffen Groth]
  • A. Dirk Nannes
    Dirk Nannes is a former Dutch-Australian fast bowler known for his successful Twenty20 career and for representing both the Netherlands and Australia in international cricket.
  • B. Carsten Dominik
    Carsten Dominik is a software developer and astronomer best known as the original creator of Org-mode for Emacs.
  • C. Hannes Messemer
    Hannes Messemer was a German actor best known for his roles in postwar European cinema, particularly in war and drama films.
  • D. Jens Meyer
    Jens Meyer is a German local politician who serves as the mayor of the Bavarian town of Weiden in der Oberpfalz.
  • E. Stefan Schmidt
    Stefan Schmidt is a German politician known for his work with the Alliance 90/The Greens party, particularly on environmental and transport policy.
  • 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: Steffen Groth
Triple: [Groth, hasNotableBearer, Steffen Groth]
Generated description
Steffen Groth is a German actor and director known for his roles in television series and films.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Steffen Groth
Target entity description: Steffen Groth is a German actor and director known for his roles in television series and films.
  • A. Dirk Nannes
    Dirk Nannes is a former Dutch-Australian fast bowler known for his successful Twenty20 career and for representing both the Netherlands and Australia in international cricket.
  • B. Carsten Dominik
    Carsten Dominik is a software developer and astronomer best known as the original creator of Org-mode for Emacs.
  • C. Hannes Messemer
    Hannes Messemer was a German actor best known for his roles in postwar European cinema, particularly in war and drama films.
  • D. Jens Meyer
    Jens Meyer is a German local politician who serves as the mayor of the Bavarian town of Weiden in der Oberpfalz.
  • E. Stefan Schmidt
    Stefan Schmidt is a German politician known for his work with the Alliance 90/The Greens party, particularly on environmental and transport policy.
  • 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_69ca84d4eddc8190996fec1417d2bae8 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9facd5b881909f0569b23f308815 completed April 1, 2026, 10:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1b020829481908456e7977c5f9adb completed April 5, 2026, 12:43 a.m.
NEDg Description generation batch_69d1b0dde93881908fcec28de9cfa99d completed April 5, 2026, 12:46 a.m.
NED2 Entity disambiguation (via description) batch_69d1b1bbe6108190af17b75f79c0f465 completed April 5, 2026, 12:50 a.m.
Created at: March 30, 2026, 8:24 p.m.