Triple

T18751668
Position Surface form Disambiguated ID Type / Status
Subject Anne McLaren E458540 entity
Predicate givenName P17 FINISHED
Object Anne
Anne is a feminine given name of Hebrew origin, commonly used in many European languages and often associated with historical and literary figures.
E267026 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: Anne | Statement: [Anne McLaren, givenName, Anne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Anne
Context triple: [Anne McLaren, givenName, Anne]
  • A. Anne
    Anne is traditionally revered in Christian tradition as the mother of the Virgin Mary and the grandmother of Jesus.
  • B. Anne
    Anne is the protagonist of "The Darkest Hour," around whom the film’s central conflict and emotional journey revolve.
  • C. Anne
    Anne is one of the central child protagonists in Enid Blyton’s Famous Five adventure series, known for her kindness, domestic sense, and cautious nature.
  • D. Anne
    Anne is one of the child protagonists in Enid Blyton’s Famous Five series, known for her cautious nature and love of home comforts during the group’s adventures.
  • E. Anne
    Anne is one of the central child protagonists in Enid Blyton’s Famous Five series, known for her kindness, domestic sense, and participation in the group’s adventurous mysteries.
  • 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: Anne
Triple: [Anne McLaren, givenName, Anne]
Generated description
Anne is a feminine given name of Hebrew origin, commonly used in many European languages and often associated with historical and literary figures.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Anne
Target entity description: Anne is a feminine given name of Hebrew origin, commonly used in many European languages and often associated with historical and literary figures.
  • A. Anne chosen
    Anne is a female given name of Hebrew origin, commonly used in many European languages and historically borne by numerous queens, saints, and notable women.
  • B. Anne
    Anne is the given name of Lady Anne Temple, a historical noblewoman likely associated with the British aristocracy.
  • C. Anne
    Anne is a given name used by Princess Marianne of Prussia, a 19th-century Prussian royal.
  • D. Anne
    Anne is the given name of Anne Morrow Lindbergh, the American author and aviator who was married to famed aviator Charles Lindbergh.
  • E. Anne
    Anne is the given name of Anne Cox Chambers, an American media proprietor, diplomat, and philanthropist.
  • 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_69d8d394dc308190b6725073f5db324c completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e579ed4e6881908791f2a6250010a6 completed April 20, 2026, 12:57 a.m.
NED1 Entity disambiguation (via context triple) batch_6a05470cbad081908db660e4f265d15e completed May 14, 2026, 3:52 a.m.
NEDg Description generation batch_6a054a07ae588190add42f9fcaafe771 completed May 14, 2026, 4:05 a.m.
NED2 Entity disambiguation (via description) batch_6a054c35fd88819087aebb97da3d83e4 completed May 14, 2026, 4:14 a.m.
Created at: April 10, 2026, 11:51 a.m.