Triple

T3845740
Position Surface form Disambiguated ID Type / Status
Subject Jane Eyre E93564 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 Eyre, givenName, Jane]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jane
Context triple: [Jane Eyre, 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. 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.
  • C. 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.
  • D. Emily
    Emily is a given name commonly used in English-speaking countries, often associated with literary, historical, and contemporary cultural figures.
  • 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_69aed96ce578819084ab16e3439976c9 completed March 9, 2026, 2:30 p.m.
NER Named-entity recognition batch_69aeebb77a488190be7fc2a1211f1f2d completed March 9, 2026, 3:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69b504122cb08190ba97ce14e8d891fc completed March 14, 2026, 6:45 a.m.
Created at: March 9, 2026, 3:18 p.m.