Triple

T37376227
Position Surface form Disambiguated ID Type / Status
Subject Anneliese Michel E927988 entity
Predicate hasPractitionerInvolved P202208 FINISHED
Object Ernst Alt
Ernst Alt was a German Catholic priest known for his controversial involvement in the 1970s exorcism case of Anneliese Michel.
 E2223430 NE FINISHED

How this triple was built (3 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: Ernst Alt | Statement: [Anneliese Michel, hasPractitionerInvolved, Ernst Alt]
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: Ernst Alt
Triple: [Anneliese Michel, hasPractitionerInvolved, Ernst Alt]
Generated description
Ernst Alt was a German Catholic priest known for his controversial involvement in the 1970s exorcism case of Anneliese Michel.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: hasPractitionerInvolved
Context triple: [Anneliese Michel, hasPractitionerInvolved, Ernst Alt]
  • A. hasPractitioners chosen
    Indicates that an entity is associated with one or more individuals who actively practice, perform, or apply it.
  • B. hasProfessionalRelationshipWith
    Indicates a formal, work-related connection or collaboration exists between the two entities in a professional context.
  • C. administeredInPracticeBy
    Indicates that a medical treatment, procedure, or intervention is carried out or delivered by a specific healthcare practice or provider entity.
  • D. hasAuthorityInvolved
    Indicates that an authority or official body is involved in, oversees, or has jurisdiction over the referenced situation or relationship.
  • E. usedMedicalPersonnel
    Indicates that an entity employed or made use of medical personnel in performing an action or providing a service.
  • F. None of above.

Provenance (6 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_69f76eb820248190a5c395ca50ad002a completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_6a037c8efcd4819088c2aeead65d93df completed May 12, 2026, 7:16 p.m.
NED1 Entity disambiguation (via context triple) batch_6a406cf2e8848190b13fa83ecbcfada2 completed June 28, 2026, 12:38 a.m.
NEDg Description generation batch_6a406da07e6c81909bcf8a7cce086fcf completed June 28, 2026, 12:41 a.m.
NED2 Entity disambiguation (via description) batch_6a406e2e5e00819097b90719f08951c8 completed June 28, 2026, 12:43 a.m.
PD Predicate disambiguation batch_6a037a13a1308190a202df66f4781855 completed May 12, 2026, 7:05 p.m.
Created at: May 3, 2026, 4:16 p.m.