Triple

T6026442
Position Surface form Disambiguated ID Type / Status
Subject Heiner Wilmer E134193 entity
Predicate givenName P17 FINISHED
Object Heiner
Heiner is a masculine given name of German origin, commonly used in German-speaking countries.
 E564843 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: Heiner | Statement: [Heiner Wilmer, givenName, Heiner]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Heiner
Context triple: [Heiner Wilmer, givenName, Heiner]
  • A. Heike Makatsch
    Heike Makatsch is a German actress and former television presenter known internationally for her roles in films such as "Love Actually" and "Resident Evil."
  • B. Moritz
    Moritz is a masculine given name of German origin, commonly used in German-speaking countries.
  • C. Hansi
    Hansi is a historic town in the Hisar district of Haryana, India, known for its ancient forts and archaeological significance.
  • D. Gottsched
    Gottsched was an 18th-century German literary critic and reformer whose rationalist poetics and efforts to standardize the German language significantly shaped early German Enlightenment literature.
  • E. Reinhard
    Reinhard is a masculine German given name historically borne by several notable figures, including high-ranking officials in Nazi Germany.
  • 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: Heiner
Triple: [Heiner Wilmer, givenName, Heiner]
Generated description
Heiner is a masculine given name of German origin, commonly used in German-speaking countries.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Heiner
Target entity description: Heiner is a masculine given name of German origin, commonly used in German-speaking countries.
  • A. Heike Makatsch
    Heike Makatsch is a German actress and former television presenter known internationally for her roles in films such as "Love Actually" and "Resident Evil."
  • B. Moritz
    Moritz is a masculine given name of German origin, commonly used in German-speaking countries.
  • C. Hansi
    Hansi is a historic town in the Hisar district of Haryana, India, known for its ancient forts and archaeological significance.
  • D. Gottsched
    Gottsched was an 18th-century German literary critic and reformer whose rationalist poetics and efforts to standardize the German language significantly shaped early German Enlightenment literature.
  • E. Reinhard
    Reinhard is a masculine German given name historically borne by several notable figures, including high-ranking officials in Nazi Germany.
  • 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_69c0087515148190a97475d412563865 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c0560cdc308190b25ca8ecb42c4e4f completed March 22, 2026, 8:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69c11375b4448190ad3087b21ac67329 completed March 23, 2026, 10:18 a.m.
NEDg Description generation batch_69c11551bec88190be77db3ec96045ad completed March 23, 2026, 10:26 a.m.
NED2 Entity disambiguation (via description) batch_69c115f88e948190a3ea11b33742779c completed March 23, 2026, 10:29 a.m.
Created at: March 22, 2026, 4:07 p.m.