Triple

T4901450
Position Surface form Disambiguated ID Type / Status
Subject Jane Adams E109806 entity
Predicate givenName P17 FINISHED
Object Jane E47230 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: Jane | Statement: [Jane Adams, givenName, Jane]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jane
Context triple: [Jane Adams, givenName, Jane]
  • A. Jane
    Jane is a powerful vampire in the Twilight series, known for her childlike appearance and her ability to inflict excruciating pain with her mind as a high-ranking enforcer of the Volturi.
  • B. Jane chosen
    Jane is a feminine given name of English origin that has been widely used in many English-speaking countries for centuries.
  • C. Emily
    Emily is a given name commonly used in English-speaking countries, often associated with literary, historical, and contemporary cultural figures.
  • D. Emily
    Emily Warren Roebling was a pioneering 19th-century American engineer best known for her crucial role in overseeing the completion of the Brooklyn Bridge.
  • E. Jennifer
    Jennifer is a common feminine given name of English origin, derived from the Cornish form of Guinevere and widely used in many English-speaking countries.
  • 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_69bd441180708190ba42ffb44fea533a completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6e4dd6bc819094b1cbf533510995 completed March 20, 2026, 3:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69be6fd2a0348190a285ea1a62e7ae1b completed March 21, 2026, 10:15 a.m.
Created at: March 20, 2026, 1:28 p.m.