Triple

T89240
Position Surface form Disambiguated ID Type / Status
Subject Sara Ann Delano Roosevelt E1793 entity
Predicate middleName P143 FINISHED
Object Ann
Ann is a given name commonly used as a feminine first or middle name in English-speaking countries.
 E33934 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: Ann | Statement: [Sara Ann Delano Roosevelt, middleName, Ann]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ann
Context triple: [Sara Ann Delano Roosevelt, middleName, Ann]
  • 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. Kathleen
    Kathleen is a feminine given name of Irish origin, derived from the name Catherine and widely used in English-speaking countries.
  • C. Emma
    Emma is a common feminine given name of Germanic origin, widely used in English-speaking and many other countries.
  • D. Nancy
    Nancy is a feminine given name of Hebrew origin meaning "grace" that became especially popular in English-speaking countries in the 20th century.
  • E. Lucille
    "Lucille" is a 1977 country song by Kenny Rogers that became one of his signature hits and a classic of the genre.
  • 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: Ann
Triple: [Sara Ann Delano Roosevelt, middleName, Ann]
Generated description
Ann is a given name commonly used as a feminine first or middle name in English-speaking countries.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ann
Target entity description: Ann is a given name commonly used as a feminine first or middle name in English-speaking 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. Kathleen
    Kathleen is a feminine given name of Irish origin, derived from the name Catherine and widely used in English-speaking countries.
  • C. Emma
    Emma is a common feminine given name of Germanic origin, widely used in English-speaking and many other countries.
  • D. Nancy
    Nancy is a feminine given name of Hebrew origin meaning "grace" that became especially popular in English-speaking countries in the 20th century.
  • E. Lucille
    "Lucille" is a 1977 country song by Kenny Rogers that became one of his signature hits and a classic of the genre.
  • 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_69a24d1a97dc819094e6c021fe9b05a7 completed Feb. 28, 2026, 2:04 a.m.
NER Named-entity recognition batch_69a383e3575c8190932dcdc25503d06e completed March 1, 2026, 12:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69a3861002e48190a2f2ac4595eb0679 completed March 1, 2026, 12:19 a.m.
NEDg Description generation batch_69a386680f5c8190a3f98e7a0505e217 completed March 1, 2026, 12:20 a.m.
NED2 Entity disambiguation (via description) batch_69a386b7d8408190bb37063b727c0f46 completed March 1, 2026, 12:22 a.m.
Created at: Feb. 28, 2026, 2:07 a.m.