Triple

T8556038
Position Surface form Disambiguated ID Type / Status
Subject Anni Albers E202565 entity
Predicate givenName P17 FINISHED
Object Annelise
Annelise is the given name of Anni Albers, the influential German-born textile artist and printmaker associated with the Bauhaus and later American modernism.
 E745011 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: Annelise | Statement: [Anni Albers, givenName, Annelise]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Annelise
Context triple: [Anni Albers, givenName, Annelise]
  • A. Alana
    Alana is a feminine given name commonly used in English-speaking countries and various cultures worldwide.
  • B. Tessa
    Tessa is a feminine given name commonly used in English-speaking countries, often as a diminutive of Theresa or Therese.
  • C. Annis
    Annis is a feminine given name of English origin, historically used in the Anglophone world.
  • D. Annalise
    Annalise is a minor but pivotal character in John le Carré’s espionage novel "Smiley’s People," involved in the intricate web of intelligence and personal relationships surrounding George Smiley.
  • E. Alessandra
    Alessandra is an Italian politician, former actress, and granddaughter of Benito Mussolini.
  • 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: Annelise
Triple: [Anni Albers, givenName, Annelise]
Generated description
Annelise is the given name of Anni Albers, the influential German-born textile artist and printmaker associated with the Bauhaus and later American modernism.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Annelise
Target entity description: Annelise is the given name of Anni Albers, the influential German-born textile artist and printmaker associated with the Bauhaus and later American modernism.
  • A. Alana
    Alana is a feminine given name commonly used in English-speaking countries and various cultures worldwide.
  • B. Tessa
    Tessa is a feminine given name commonly used in English-speaking countries, often as a diminutive of Theresa or Therese.
  • C. Annis
    Annis is a feminine given name of English origin, historically used in the Anglophone world.
  • D. Annalise
    Annalise is a minor but pivotal character in John le Carré’s espionage novel "Smiley’s People," involved in the intricate web of intelligence and personal relationships surrounding George Smiley.
  • E. Alessandra
    Alessandra is an Italian politician, former actress, and granddaughter of Benito Mussolini.
  • 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_69ca832610e08190b3b6c6cd2c250255 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe88bcce081909e12e4037a0e6323 completed March 31, 2026, 3:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69cea868de6881908e87270a1fea0e4b completed April 2, 2026, 5:33 p.m.
NEDg Description generation batch_69cea9cff1ec8190a0093fb42782341e completed April 2, 2026, 5:39 p.m.
NED2 Entity disambiguation (via description) batch_69ceaa9f7f8c8190965e86880ff141d5 completed April 2, 2026, 5:42 p.m.
Created at: March 30, 2026, 6:19 p.m.