Triple

T8476255
Position Surface form Disambiguated ID Type / Status
Subject Lara Logan E200400 entity
Predicate givenName P17 FINISHED
Object Lara E77944 NE FINISHED

How this triple was built (2 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 Logan, givenName, Lara]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lara
Context triple: [Lara Logan, givenName, Lara]
  • A. Lara chosen
    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.
  • B. Lara
    Lara is a semi-autobiographical novel by British writer Bernardine Evaristo that explores themes of identity, heritage, and family across generations.
  • C. Lara Sanoica
    Lara Sanoica is an American local politician who serves as the mayor of Rolling Meadows, Illinois.
  • D. Lara Belmont
    Lara Belmont is a British actress best known for her role in the war drama film "The War Zone."
  • E. Lara, Victoria
    Lara, Victoria is a regional township in the City of Greater Geelong, Australia, known as a growing commuter suburb between Melbourne and Geelong.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ca831b17988190a1f3f3413d57b820 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe51e21548190811e3c7ba7b196e5 completed March 31, 2026, 3:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce3a0f5e088190b70b2c7437884b3b completed April 2, 2026, 9:42 a.m.
Created at: March 30, 2026, 6:12 p.m.