Triple

T7937613
Position Surface form Disambiguated ID Type / Status
Subject systemd E184322 entity
Predicate developer P73 FINISHED
Object Lennart Poettering
Lennart Poettering is a German software engineer best known for creating the systemd init system and contributing extensively to Linux userspace infrastructure.
E699701 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: Lennart Poettering | Statement: [systemd, developer, Lennart Poettering]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lennart Poettering
Context triple: [systemd, developer, Lennart Poettering]
  • A. Christian Scholz
    Christian Scholz is a German computer scientist and open-source developer known for his contributions to web technologies and social software.
  • B. Florian Haertel
    Florian Haertel is a German journalist and photographer best known as the former husband of British actress Alex Kingston.
  • C. Martin Schröder
    Martin Schröder is a Dutch aviation entrepreneur best known as the founder of the charter airline Martinair.
  • D. Florian Ballhaus
    Florian Ballhaus is a German cinematographer known for his work on major Hollywood films and television series.
  • E. Werner Maas
    Werner Maas was a microbiologist associated with the influential mid-20th-century Phage Group that helped establish modern molecular genetics.
  • 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: Lennart Poettering
Triple: [systemd, developer, Lennart Poettering]
Generated description
Lennart Poettering is a German software engineer best known for creating the systemd init system and contributing extensively to Linux userspace infrastructure.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Lennart Poettering
Target entity description: Lennart Poettering is a German software engineer best known for creating the systemd init system and contributing extensively to Linux userspace infrastructure.
  • A. Christian Scholz
    Christian Scholz is a German computer scientist and open-source developer known for his contributions to web technologies and social software.
  • B. Florian Haertel
    Florian Haertel is a German journalist and photographer best known as the former husband of British actress Alex Kingston.
  • C. Martin Schröder
    Martin Schröder is a Dutch aviation entrepreneur best known as the founder of the charter airline Martinair.
  • D. Florian Ballhaus
    Florian Ballhaus is a German cinematographer known for his work on major Hollywood films and television series.
  • E. Werner Maas
    Werner Maas was a microbiologist associated with the influential mid-20th-century Phage Group that helped establish modern molecular genetics.
  • 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_69ca8290c21c8190906a5ca6fe2b03c4 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb3aef2394819086eea1f6ab117aed completed March 31, 2026, 3:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69cb5c0a96ac819099ad30fb925eb329 completed March 31, 2026, 5:30 a.m.
NEDg Description generation batch_69cb7634f4dc8190b5e537f24bccd651 completed March 31, 2026, 7:22 a.m.
NED2 Entity disambiguation (via description) batch_69cbb67e77a48190b93c6ba61becfac4 completed March 31, 2026, 11:56 a.m.
Created at: March 30, 2026, 5:08 p.m.