Triple

T1727216
Position Surface form Disambiguated ID Type / Status
Subject Jane Austen E37524 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 Austen, givenName, Jane]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jane
Context triple: [Jane Austen, givenName, Jane]
  • A. Jane chosen
    Jane is a feminine given name of English origin that has been widely used in many English-speaking countries for centuries.
  • B. 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.
  • C. 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.
  • D. Jenny
    "Jenny" is a narrative poem by Dante Gabriel Rossetti that explores themes of desire, morality, and Victorian attitudes toward prostitution through a reflective monologue addressed to a fallen woman.
  • E. Emma
    Emma is a common feminine given name of Germanic origin, widely used in English-speaking and many other 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_69a8861acab88190bb43cde203429399 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa637c26988190ad5c400856684825 completed March 6, 2026, 5:17 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae030371e88190982c822a460d3e47 completed March 8, 2026, 11:15 p.m.
Created at: March 4, 2026, 7:30 p.m.