Triple

T167888
Position Surface form Disambiguated ID Type / Status
Subject Emma Thompson E3055 entity
Predicate givenName P17 FINISHED
Object Emma
Emma is a common feminine given name of Germanic origin, widely used in English-speaking and many other countries.
 E30843 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: Emma | Statement: [Emma Thompson, givenName, Emma]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Emma
Context triple: [Emma Thompson, givenName, Emma]
  • A. Anna
    Anna is the given first name of Eleanor Roosevelt, the influential former First Lady of the United States and human rights advocate.
  • B. Jamie
    Jamie is a given name commonly used as a diminutive or variant of James, and is borne by people of all genders in English-speaking countries.
  • C. Abigail
    Abigail is a feminine given name of Hebrew origin meaning "my father is joy," historically popular in English-speaking countries.
  • D. Joanna
    Joanna is the first name of Joanna Newsom, an American harpist, singer-songwriter, and musician known for her intricate compositions and distinctive vocal style.
  • E. Kathleen
    Kathleen is a feminine given name of Irish origin, derived from the name Catherine and widely used in English-speaking countries.
  • 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: Emma
Triple: [Emma Thompson, givenName, Emma]
Generated description
Emma is a common feminine given name of Germanic origin, widely used in English-speaking and many other countries.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Emma
Target entity description: Emma is a common feminine given name of Germanic origin, widely used in English-speaking and many other countries.
  • A. Anna
    Anna is the given first name of Eleanor Roosevelt, the influential former First Lady of the United States and human rights advocate.
  • B. Jamie
    Jamie is a given name commonly used as a diminutive or variant of James, and is borne by people of all genders in English-speaking countries.
  • C. Abigail
    Abigail is a feminine given name of Hebrew origin meaning "my father is joy," historically popular in English-speaking countries.
  • D. Joanna
    Joanna is the first name of Joanna Newsom, an American harpist, singer-songwriter, and musician known for her intricate compositions and distinctive vocal style.
  • E. Kathleen
    Kathleen is a feminine given name of Irish origin, derived from the name Catherine and widely used in English-speaking countries.
  • 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_69a2524ce1e48190ab066bf72859f474 completed Feb. 28, 2026, 2:26 a.m.
NER Named-entity recognition batch_69a258b58efc8190959c86f73d67b744 completed Feb. 28, 2026, 2:53 a.m.
NED1 Entity disambiguation (via context triple) batch_69a3672cae0c819086233f16cc2003de completed Feb. 28, 2026, 10:07 p.m.
NEDg Description generation batch_69a367aa62f481908414358a21667187 completed Feb. 28, 2026, 10:09 p.m.
NED2 Entity disambiguation (via description) batch_69a3686970ac81908ba7efe90feb26fd completed Feb. 28, 2026, 10:12 p.m.
Created at: Feb. 28, 2026, 2:34 a.m.