Triple

T622168
Position Surface form Disambiguated ID Type / Status
Subject Lara Trump E14536 entity
Predicate givenName P17 FINISHED
Object Lara
Lara is a feminine given name, often used in various cultures and languages, sometimes as a variant of Laura or derived from Latin and Russian origins.
 E77944 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: Lara | Statement: [Lara Trump, givenName, Lara]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lara
Context triple: [Lara Trump, givenName, Lara]
  • A. Diana
    Diana is a feminine given name of Latin origin, famously borne by the Roman goddess of the hunt and by Diana, Princess of Wales.
  • B. Rachel
    Rachel is a prominent biblical matriarch in the Book of Genesis, known as Jacob’s beloved wife and the mother of Joseph and Benjamin.
  • C. Zora
    Zora is a feminine given name most famously associated with the African-American author and anthropologist Zora Neale Hurston.
  • D. Mara
    Mara is a surname of Irish origin borne by various notable individuals in fields such as sports, entertainment, and politics.
  • E. Pauletta
    Pauletta is a feminine given name, typically considered a diminutive or variant of Paula or Pauline.
  • 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: Lara
Triple: [Lara Trump, givenName, Lara]
Generated description
Lara is a feminine given name, often used in various cultures and languages, sometimes as a variant of Laura or derived from Latin and Russian origins.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lara
Target entity description: Lara is a feminine given name, often used in various cultures and languages, sometimes as a variant of Laura or derived from Latin and Russian origins.
  • A. Diana
    Diana is a feminine given name of Latin origin, famously borne by the Roman goddess of the hunt and by Diana, Princess of Wales.
  • B. Rachel
    Rachel is a prominent biblical matriarch in the Book of Genesis, known as Jacob’s beloved wife and the mother of Joseph and Benjamin.
  • C. Zora
    Zora is a feminine given name most famously associated with the African-American author and anthropologist Zora Neale Hurston.
  • D. Mara
    Mara is a surname of Irish origin borne by various notable individuals in fields such as sports, entertainment, and politics.
  • E. Pauletta
    Pauletta is a feminine given name, typically considered a diminutive or variant of Paula or Pauline.
  • 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_69a4934b17c881909ace8270e8ddd202 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a49e402d9c8190936896e3ebb6edc5 completed March 1, 2026, 8:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69a563cab73c819082b51d64d249143b completed March 2, 2026, 10:17 a.m.
NEDg Description generation batch_69a5657b51c881909c393f79c359181c completed March 2, 2026, 10:24 a.m.
NED2 Entity disambiguation (via description) batch_69a565e528a88190a547f69c7e378140 completed March 2, 2026, 10:26 a.m.
Created at: March 1, 2026, 7:35 p.m.