Triple

T23289054
Position Surface form Disambiguated ID Type / Status
Subject Johanna Fiedler E589975 entity
Predicate givenName P17 FINISHED
Object Johanna
Johanna is a feminine given name of Hebrew origin, commonly used in various European languages and often associated with forms like Joanna or Joan.
E1155847 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: Johanna | Statement: [Johanna Fiedler, givenName, Johanna]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Johanna
Context triple: [Johanna Fiedler, givenName, Johanna]
  • A. Johanna
    Johanna is the birth name of Frieda Lawrence, the German-born writer and wife of English novelist D. H. Lawrence.
  • B. Johanna
    Johanna is the given name of Johanna Spyri, the Swiss author best known for creating the classic children's novel "Heidi."
  • C. Johanna
    "Johanna" is a recurring, lyrically poignant love song from Stephen Sondheim's musical *Sweeney Todd: The Demon Barber of Fleet Street*.
  • D. Johanna
    Johanna is the birth name of Magda Goebbels, the wife of Nazi propaganda minister Joseph Goebbels and a prominent figure in Nazi Germany.
  • E. Johanna
    Johanna is a Hungarian experimental opera film reimagining the story of Joan of Arc in a modern hospital setting, directed by Kornél Mundruczó.
  • 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: Johanna
Triple: [Johanna Fiedler, givenName, Johanna]
Generated description
Johanna is a feminine given name of Hebrew origin, commonly used in various European languages and often associated with forms like Joanna or Joan.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Johanna
Target entity description: Johanna is a feminine given name of Hebrew origin, commonly used in various European languages and often associated with forms like Joanna or Joan.
  • A. Johanna chosen
    Johanna is a feminine given name of Hebrew origin, commonly used in many European languages and derived from a form of "Johannes" meaning "God is gracious."
  • B. Johanna
    Johanna is the given name of Johanna Spyri, the Swiss author best known for creating the classic children's novel "Heidi."
  • C. Johanna
    Johanna is the birth name of Magda Goebbels, the wife of Nazi propaganda minister Joseph Goebbels and a prominent figure in Nazi Germany.
  • D. Johanna
    Johanna is the birth name of Frieda Lawrence, the German-born writer and wife of English novelist D. H. Lawrence.
  • E. Johanna
    Johanna is a Hungarian experimental opera film reimagining the story of Joan of Arc in a modern hospital setting, directed by Kornél Mundruczó.
  • 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_69e25d1af9d88190a0b9b5e8fa608618 completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f19649570c8190b565fafa55b1f886 completed April 29, 2026, 5:25 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0c4c8c2f9081908123a02dcc37ea30 completed May 19, 2026, 11:42 a.m.
NEDg Description generation batch_6a0c4ee292f08190a44326d433f37c65 completed May 19, 2026, 11:52 a.m.
NED2 Entity disambiguation (via description) batch_6a0c4f796b688190a8971ebd238e08f2 completed May 19, 2026, 11:54 a.m.
Created at: April 17, 2026, 5:01 p.m.