Triple

T14266113
Position Surface form Disambiguated ID Type / Status
Subject Gesundbrunnen E353647 entity
Predicate borderedByLocality P68061 FINISHED
Object Wedding E71194 NE FINISHED

How this triple was built (2 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: Wedding | Statement: [Gesundbrunnen, borderedByLocality, Wedding]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wedding
Context triple: [Gesundbrunnen, borderedByLocality, Wedding]
  • A. Wedding chosen
    Wedding is a district in Berlin, Germany, known for its multicultural character and urban residential neighborhoods.
  • B. Wedding Day
    "Wedding Day" is a notable poem by Harlem Renaissance writer and artist Gwendolyn Bennett, reflecting her lyrical style and exploration of Black identity and emotional experience.
  • C. Wedding Day
    "Wedding Day" is a short story by Ernest Hemingway that follows his recurring character Nick Adams through the emotional complexities surrounding marriage and personal relationships.
  • D. Anand Karaj
    Anand Karaj is the Sikh marriage ceremony, conducted in the presence of the Guru Granth Sahib and centered on spiritual union and commitment.
  • E. Royal Wedding
    Royal Wedding is a 1951 MGM musical film starring Fred Astaire, renowned for its innovative dance sequences including Astaire’s iconic ceiling-and-walls dance.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d8278c43e08190824146f4632b89a5 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de6357a8188190ba518a486521052b completed April 14, 2026, 3:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd3d16bae881909b38ccf04f1cf823 completed May 8, 2026, 1:32 a.m.
Created at: April 10, 2026, 1:09 a.m.