Triple

T8735597
Position Surface form Disambiguated ID Type / Status
Subject Gisela Stuart E207374 entity
Predicate givenName P17 FINISHED
Object Gisela
Gisela is a feminine given name of Germanic origin, commonly used in German-speaking and other European countries.
 E260312 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: Gisela | Statement: [Gisela Stuart, givenName, Gisela]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Gisela
Context triple: [Gisela Stuart, givenName, Gisela]
  • A. Gisela
    Gisela was a daughter of Charlemagne, the Frankish king and first Holy Roman Emperor, and a member of the Carolingian royal family.
  • B. Ricarda
    Ricarda is a feminine given name, primarily used in German- and Spanish-speaking countries, derived from the male name Richard.
  • C. Ottla
    Ottla was the beloved younger sister of writer Franz Kafka, known from his diaries and letters for her close relationship with him and her tragic death in the Holocaust.
  • D. Franziska
    Franziska is a feminine given name of German origin, closely related to and cognate with the name Frances.
  • E. Hedvig
    Hedvig is a Scandinavian female given name, historically borne by several notable women in Swedish and broader Nordic royalty and nobility.
  • 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: Gisela
Triple: [Gisela Stuart, givenName, Gisela]
Generated description
Gisela is a feminine given name of Germanic origin, commonly used in German-speaking and other European countries.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Gisela
Target entity description: Gisela is a feminine given name of Germanic origin, commonly used in German-speaking and other European countries.
  • A. Gisela chosen
    Gisela was a daughter of Charlemagne, the Frankish king and first Holy Roman Emperor, and a member of the Carolingian royal family.
  • B. Ricarda
    Ricarda is a feminine given name, primarily used in German- and Spanish-speaking countries, derived from the male name Richard.
  • C. Ottla
    Ottla was the beloved younger sister of writer Franz Kafka, known from his diaries and letters for her close relationship with him and her tragic death in the Holocaust.
  • D. Franziska
    Franziska is a feminine given name of German origin, closely related to and cognate with the name Frances.
  • E. Hedvig
    Hedvig is a Scandinavian female given name, historically borne by several notable women in Swedish and broader Nordic royalty and nobility.
  • 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_69ca835a03a081909d4d4cd01a18c9fb completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5d44275881909f7eb40b24180294 completed March 31, 2026, 11:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf42bd840081908074e9d322a15b68 completed April 3, 2026, 4:31 a.m.
NEDg Description generation batch_69cf44b3ce2c8190b109189990ae6564 completed April 3, 2026, 4:40 a.m.
NED2 Entity disambiguation (via description) batch_69cf4578473081909fc55632c366a56a completed April 3, 2026, 4:43 a.m.
Created at: March 30, 2026, 6:37 p.m.