Triple

T18682247
Position Surface form Disambiguated ID Type / Status
Subject Holzwickede E456761 entity
Predicate hasSubdivision P747 FINISHED
Object Hengsen
Hengsen is a village-level district of the municipality of Holzwickede in North Rhine-Westphalia, Germany.
E1337394 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: Hengsen | Statement: [Holzwickede, hasSubdivision, Hengsen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hengsen
Context triple: [Holzwickede, hasSubdivision, Hengsen]
  • A. Hengchi
    Hengchi is an electric vehicle brand developed by the Chinese conglomerate Evergrande Group as part of its push into the new energy automotive industry.
  • B. Heng
    Heng is a small tidal island off the coast of the Isle of Strand, known for its rugged shoreline and natural coastal scenery.
  • C. Weihan
    Weihan is a Chinese given name most notably borne by Li Weihan, a prominent Chinese Communist revolutionary and politician.
  • D. Jianhua
    Jianhua is a common Chinese given name shared by many individuals across different fields.
  • E. Yongrong
    Yongrong was a Qing dynasty imperial prince, known as one of the sons of the Qianlong Emperor and a member of the high Manchu nobility.
  • 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: Hengsen
Triple: [Holzwickede, hasSubdivision, Hengsen]
Generated description
Hengsen is a village-level district of the municipality of Holzwickede in North Rhine-Westphalia, Germany.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Hengsen
Target entity description: Hengsen is a village-level district of the municipality of Holzwickede in North Rhine-Westphalia, Germany.
  • A. Hengchi
    Hengchi is an electric vehicle brand developed by the Chinese conglomerate Evergrande Group as part of its push into the new energy automotive industry.
  • B. Heng
    Heng is a small tidal island off the coast of the Isle of Strand, known for its rugged shoreline and natural coastal scenery.
  • C. Weihan
    Weihan is a Chinese given name most notably borne by Li Weihan, a prominent Chinese Communist revolutionary and politician.
  • D. Jianhua
    Jianhua is a common Chinese given name shared by many individuals across different fields.
  • E. Yongrong
    Yongrong was a Qing dynasty imperial prince, known as one of the sons of the Qianlong Emperor and a member of the high Manchu nobility.
  • 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_69d8d391eb488190ac2e9abf5bf255e4 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e55b2906ec8190ad8db8e3ae6b2945 completed April 19, 2026, 10:46 p.m.
NED1 Entity disambiguation (via context triple) batch_6a052358206c81908fd07af6b2911400 completed May 14, 2026, 1:20 a.m.
NEDg Description generation batch_6a05246d04408190995d7e34f6662011 completed May 14, 2026, 1:25 a.m.
NED2 Entity disambiguation (via description) batch_6a0524eced608190a1b3468f6d0189c2 completed May 14, 2026, 1:27 a.m.
Created at: April 10, 2026, 11:49 a.m.