Triple

T497062
Position Surface form Disambiguated ID Type / Status
Subject Laurene Powell Jobs E10316 entity
Predicate givenName P17 FINISHED
Object Laurene
Laurene is the first name of Laurene Powell Jobs, an American businesswoman, philanthropist, and widow of Apple co-founder Steve Jobs.
 E64926 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: Laurene | Statement: [Laurene Powell Jobs, givenName, Laurene]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Laurene
Context triple: [Laurene Powell Jobs, givenName, Laurene]
  • A. Kathleen
    Kathleen is a feminine given name of Irish origin, derived from the name Catherine and widely used in English-speaking countries.
  • B. Linda
    Linda is a feminine given name of Germanic origin that became widely used in English-speaking countries in the 20th century.
  • C. Paula
    Paula is a feminine given name used in many languages, derived from the Latin name Paulus meaning "small" or "humble."
  • D. Kathryn
    Kathryn is a feminine given name, commonly considered a variant spelling of Katherine/Catherine.
  • E. Nancy
    Nancy is a feminine given name of Hebrew origin meaning "grace" that became especially popular in English-speaking countries in the 20th century.
  • 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: Laurene
Triple: [Laurene Powell Jobs, givenName, Laurene]
Generated description
Laurene is the first name of Laurene Powell Jobs, an American businesswoman, philanthropist, and widow of Apple co-founder Steve Jobs.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Laurene
Target entity description: Laurene is the first name of Laurene Powell Jobs, an American businesswoman, philanthropist, and widow of Apple co-founder Steve Jobs.
  • A. Kathleen
    Kathleen is a feminine given name of Irish origin, derived from the name Catherine and widely used in English-speaking countries.
  • B. Linda
    Linda is a feminine given name of Germanic origin that became widely used in English-speaking countries in the 20th century.
  • C. Paula
    Paula is a feminine given name used in many languages, derived from the Latin name Paulus meaning "small" or "humble."
  • D. Kathryn
    Kathryn is a feminine given name, commonly considered a variant spelling of Katherine/Catherine.
  • E. Nancy
    Nancy is a feminine given name of Hebrew origin meaning "grace" that became especially popular in English-speaking countries in the 20th century.
  • 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_69a2e847df8481909239ec08ccf1e376 completed Feb. 28, 2026, 1:06 p.m.
NER Named-entity recognition batch_69a2f116f1b4819082f88d6c747368ae completed Feb. 28, 2026, 1:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69a4a6fa632881908ab09767610e6a37 completed March 1, 2026, 8:52 p.m.
NEDg Description generation batch_69a4a7c98d60819099502bbce8d45943 completed March 1, 2026, 8:55 p.m.
NED2 Entity disambiguation (via description) batch_69a4a8359edc8190a1d8986cb50c457b completed March 1, 2026, 8:57 p.m.
Created at: Feb. 28, 2026, 1:12 p.m.