Triple

T10908994
Position Surface form Disambiguated ID Type / Status
Subject Anne Mulcahy E257643 entity
Predicate givenName P17 FINISHED
Object Anne
Anne is a feminine given name of Hebrew origin, commonly used in English-speaking countries and often associated with grace and favor.
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 Mulcahy, givenName, Anne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Anne
Context triple: [Anne Mulcahy, 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 was the Queen of Great Britain and Ireland from 1702 to 1714, the last monarch of the House of Stuart.
  • 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 Mulcahy, givenName, Anne]
Generated description
Anne is a feminine given name of Hebrew origin, commonly used in English-speaking countries and often associated with grace and favor.
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 English-speaking countries and often associated with grace and favor.
  • 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 Anne Morrow Lindbergh, the American author and aviator who was married to famed aviator Charles Lindbergh.
  • C. Anne
    Anne is traditionally revered in Christian tradition as the mother of the Virgin Mary and the grandmother of Jesus.
  • D. Anne
    Anne is the birth name of Nancy Reagan, the former First Lady of the United States and wife of President Ronald Reagan.
  • E. 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.
  • 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_69d6aa8550c8819095508a2ed9acf3db completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d7706824d08190ba894d144cc6b3ba completed April 9, 2026, 9:24 a.m.
NED1 Entity disambiguation (via context triple) batch_69e154a582188190af96ae0d5cc08dc4 completed April 16, 2026, 9:29 p.m.
NEDg Description generation batch_69e1739ed9b88190949125759f42efd2 completed April 16, 2026, 11:41 p.m.
NED2 Entity disambiguation (via description) batch_69e175ecef0c8190b08052d751f1a608 completed April 16, 2026, 11:51 p.m.
Created at: April 8, 2026, 9:22 p.m.