Triple

T2222379
Position Surface form Disambiguated ID Type / Status
Subject Laurence E48169 entity
Predicate hasRelatedName P3889 FINISHED
Object Laurie E135112 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: Laurie | Statement: [Laurence, hasRelatedName, Laurie]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Laurie
Context triple: [Laurence, hasRelatedName, Laurie]
  • A. Lori chosen
    Lori is a feminine given name commonly used in English-speaking countries, often as a diminutive of Laura or Lorraine.
  • B. Linda
    Linda is a feminine given name of Germanic origin that became widely used in English-speaking countries in the 20th century.
  • C. Lauren
    Lauren is a central female protagonist in the romantic comedy film "Think Like a Man," portrayed as a successful, relationship-seeking woman whose love life is influenced by Steve Harvey’s dating advice.
  • D. Suzanne
    "Suzanne" is a renowned song by Leonard Cohen, celebrated for its poetic lyrics and haunting melody.
  • E. Molly Stark
    Molly Stark was the wife of American Revolutionary War General John Stark, remembered in part through his famous battle cry invoking her name at the Battle of Bennington.
  • 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_69a88aa1ee708190862c8c378c41e9eb completed March 4, 2026, 7:40 p.m.
NER Named-entity recognition batch_69abc03bfdd48190bfb96ec3e41c22dc completed March 7, 2026, 6:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69af5cc3255c8190bc8de265f452a6b0 completed March 9, 2026, 11:50 p.m.
Created at: March 4, 2026, 7:47 p.m.