Triple

T14764767
Position Surface form Disambiguated ID Type / Status
Subject Anne Mortimer E346964 entity
Predicate givenName P17 FINISHED
Object Anne
Anne is a feminine given name of Hebrew origin, commonly associated with grace and widely used across many cultures and languages.
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 Mortimer, givenName, Anne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Anne
Context triple: [Anne Mortimer, 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 the protagonist of "The Darkest Hour," around whom the film’s central conflict and emotional journey revolve.
  • D. 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.
  • E. 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.
  • 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 Mortimer, givenName, Anne]
Generated description
Anne is a feminine given name of Hebrew origin, commonly associated with grace and widely used across many cultures and languages.
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 associated with grace and widely used across many cultures and languages.
  • 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 the middle name of Loretta Anne Rogers, a prominent Canadian businesswoman and philanthropist associated with the Rogers telecommunications family.
  • D. Anne
    Anne is the given name of Anne Hilarion de Costentin de Tourville, a renowned French naval commander of the late 17th and early 18th centuries.
  • E. Anne
    Anne is traditionally revered in Christian tradition as the mother of the Virgin Mary and the grandmother of Jesus.
  • 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_69d822e8896c819091169882f9b20486 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69dec7f3a1608190b1b17624003a0c7f completed April 14, 2026, 11:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe24b1ff0c81908d5dffbaf86c3ca3 completed May 8, 2026, 6 p.m.
NEDg Description generation batch_69fe2689cae08190a116c5bef5341bb1 completed May 8, 2026, 6:08 p.m.
NED2 Entity disambiguation (via description) batch_69fe27149f688190ba8a531bb458c3a9 completed May 8, 2026, 6:10 p.m.
Created at: April 10, 2026, 1:30 a.m.