Triple

T10737927
Position Surface form Disambiguated ID Type / Status
Subject Annabel Davis-Goff E253243 entity
Predicate givenName P17 FINISHED
Object Annabel
Annabel is a feminine given name of Latin origin, commonly interpreted to mean "lovable" or "graceful."
 E883718 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: Annabel | Statement: [Annabel Davis-Goff, givenName, Annabel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Annabel
Context triple: [Annabel Davis-Goff, givenName, Annabel]
  • A. Maud
    Maud was a Norwegian polar exploration ship used by Roald Amundsen during his Arctic expeditions in the early 20th century.
  • B. Maud
    Maud is a small village in Aberdeenshire, Scotland, known historically as a rural railway junction and agricultural center.
  • C. Maud
    Maud is a feminine given name of Germanic origin, historically borne by European royalty and nobility.
  • D. Muriel
    Muriel is a feminine given name of French origin that has been borne by various notable figures, including politicians, writers, and artists.
  • E. Annabella
    Annabella was a French film actress of the 1930s and 1940s, known for her work in both European and Hollywood cinema.
  • 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: Annabel
Triple: [Annabel Davis-Goff, givenName, Annabel]
Generated description
Annabel is a feminine given name of Latin origin, commonly interpreted to mean "lovable" or "graceful."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Annabel
Target entity description: Annabel is a feminine given name of Latin origin, commonly interpreted to mean "lovable" or "graceful."
  • A. Maud
    Maud was a Norwegian polar exploration ship used by Roald Amundsen during his Arctic expeditions in the early 20th century.
  • B. Maud
    Maud is a small village in Aberdeenshire, Scotland, known historically as a rural railway junction and agricultural center.
  • C. Maud
    Maud is a feminine given name of Germanic origin, historically borne by European royalty and nobility.
  • D. Muriel
    Muriel is a feminine given name of French origin that has been borne by various notable figures, including politicians, writers, and artists.
  • E. Annabella
    Annabella was a French film actress of the 1930s and 1940s, known for her work in both European and Hollywood cinema.
  • 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_69d6aa5e51e8819095f06881cecf152e completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d710410a04819090036597ac0d271c completed April 9, 2026, 2:34 a.m.
NED1 Entity disambiguation (via context triple) batch_69de22dce1cc8190a3511d86e8bd6d3e completed April 14, 2026, 11:19 a.m.
NEDg Description generation batch_69de271e2698819093bba748a0a0db5d completed April 14, 2026, 11:38 a.m.
NED2 Entity disambiguation (via description) batch_69de2cdd79608190bad8045939556bc7 completed April 14, 2026, 12:02 p.m.
Created at: April 8, 2026, 9:14 p.m.