Triple

T13107377
Position Surface form Disambiguated ID Type / Status
Subject Felix Jaehn E310878 entity
Predicate associatedAct P37 FINISHED
Object OMI
OMI is a Jamaican singer and songwriter best known for his global hit single "Cheerleader."
 E1023431 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: OMI | Statement: [Felix Jaehn, associatedAct, OMI]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: OMI
Context triple: [Felix Jaehn, associatedAct, OMI]
  • A. OMI
    OMI is a Roman Catholic religious congregation of priests and brothers, formally known as the Missionary Oblates of Mary Immaculate, dedicated especially to missionary work among the poor and marginalized.
  • B. OMiK
    OMiK is the OSCE’s field mission in Kosovo, focused on promoting human rights, democratic institutions, and the rule of law.
  • C. Omni
    Omni is a short book in the Book of Mormon that continues the historical and spiritual record of the Nephite people through a series of brief entries by multiple authors.
  • D. OM
    OM is the post-nominal abbreviation used by recipients of the Order of the Cross of Terra Mariana, a high state decoration of Estonia typically awarded to foreign dignitaries for services to the Estonian state.
  • E. OM
    OM is the commonly used abbreviation for Olympique de Marseille, a major French professional football club based in Marseille.
  • 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: OMI
Triple: [Felix Jaehn, associatedAct, OMI]
Generated description
OMI is a Jamaican singer and songwriter best known for his global hit single "Cheerleader."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: OMI
Target entity description: OMI is a Jamaican singer and songwriter best known for his global hit single "Cheerleader."
  • A. OMI
    OMI is a Roman Catholic religious congregation of priests and brothers, formally known as the Missionary Oblates of Mary Immaculate, dedicated especially to missionary work among the poor and marginalized.
  • B. OMiK
    OMiK is the OSCE’s field mission in Kosovo, focused on promoting human rights, democratic institutions, and the rule of law.
  • C. Omni
    Omni is a short book in the Book of Mormon that continues the historical and spiritual record of the Nephite people through a series of brief entries by multiple authors.
  • D. OM
    OM is the post-nominal abbreviation used by recipients of the Order of the Cross of Terra Mariana, a high state decoration of Estonia typically awarded to foreign dignitaries for services to the Estonian state.
  • E. OM
    OM is the commonly used abbreviation for Olympique de Marseille, a major French professional football club based in Marseille.
  • 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_69d806a872d08190a329806f8ff30df4 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d9817ce07881909ec552bf861ac175 completed April 10, 2026, 11:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6e27a325c8190a5c0f1a582340078 completed May 3, 2026, 5:51 a.m.
NEDg Description generation batch_69f6e6a8b15081908d80cd63b0c423f6 completed May 3, 2026, 6:09 a.m.
NED2 Entity disambiguation (via description) batch_69f6e7490cc48190b596338cd3a0fd22 completed May 3, 2026, 6:12 a.m.
Created at: April 9, 2026, 9:05 p.m.