Triple

T1595583
Position Surface form Disambiguated ID Type / Status
Subject Frances Anne Emily Vane E34274 entity
Predicate givenName P17 FINISHED
Object Frances E12143 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: Frances | Statement: [Frances Anne Emily Vane, givenName, Frances]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Frances
Context triple: [Frances Anne Emily Vane, givenName, Frances]
  • A. Frances chosen
    Frances is a feminine given name of Latin origin, commonly used in English-speaking countries.
  • B. Clare
    Clare is a central character in the Restoration comedy "The Witty Fair One," known for embodying the play’s themes of wit, romance, and social intrigue.
  • C. Niles
    Niles is a historic former town in California, now a district of Fremont, known for its early silent film industry and railroad heritage.
  • D. Collier
    Collier is a surname most prominently associated in sports with Napheesa Collier, an American professional basketball player and WNBA All-Star.
  • E. Mari
    Mari is a character in Paulo Coelho's novel "Veronika Decides to Die," portrayed as a fellow patient in the mental institution who struggles with anxiety and societal expectations.
  • 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_69a885fdcb9c819081ce6f0b8cd477dd completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a9092ccb388190b2f3ed86b3853651 completed March 5, 2026, 4:40 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad46a595488190a73cfa867595b568 completed March 8, 2026, 9:51 a.m.
Created at: March 4, 2026, 7:27 p.m.