Triple

T1713126
Position Surface form Disambiguated ID Type / Status
Subject Xander E37227 entity
Predicate hasRelatedName P3889 FINISHED
Object Sander
Sander is a given name, often used as a short form of Alexander in various European countries.
 E136997 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: Sander | Statement: [Xander, hasRelatedName, Sander]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Sander
Context triple: [Xander, hasRelatedName, Sander]
  • A. Schalk
    Schalk is a masculine given name of Afrikaans and Dutch origin, commonly used in South Africa.
  • B. Sander Loones
    Sander Loones is a Belgian politician and member of the New Flemish Alliance (N-VA) who has served in both national and European political roles.
  • C. Janson
    Janson is a surname and given name of European origin, often considered a variant of Jackson.
  • D. Sven
    Sven is the lovable reindeer companion in Disney's animated film "Frozen," known for his close bond with Kristoff and his expressive, dog-like personality.
  • E. Martz
    Martz is a surname most notably associated with Mike Martz, an American football coach known for his innovative offensive strategies in the NFL.
  • 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: Sander
Triple: [Xander, hasRelatedName, Sander]
Generated description
Sander is a given name, often used as a short form of Alexander in various European countries.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Sander
Target entity description: Sander is a given name, often used as a short form of Alexander in various European countries.
  • A. Schalk
    Schalk is a masculine given name of Afrikaans and Dutch origin, commonly used in South Africa.
  • B. Sander Loones chosen
    Sander Loones is a Belgian politician and member of the New Flemish Alliance (N-VA) who has served in both national and European political roles.
  • C. Janson
    Janson is a surname and given name of European origin, often considered a variant of Jackson.
  • D. Sven
    Sven is the lovable reindeer companion in Disney's animated film "Frozen," known for his close bond with Kristoff and his expressive, dog-like personality.
  • E. Martz
    Martz is a surname most notably associated with Mike Martz, an American football coach known for his innovative offensive strategies in the NFL.
  • F. None of above.

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_69a8861912dc8190931af43b4b9158a7 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa63174b3c8190bd2406c78407be28 completed March 6, 2026, 5:16 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad8ae10a048190b7a39e4fb4fbe224 completed March 8, 2026, 2:42 p.m.
NEDg Description generation batch_69ad957adf1c8190b7c8656c1984f998 completed March 8, 2026, 3:27 p.m.
NED2 Entity disambiguation (via description) batch_69ad97af6b388190b2af293599108df3 completed March 8, 2026, 3:37 p.m.
Created at: March 4, 2026, 7:30 p.m.