Triple

T1165745
Position Surface form Disambiguated ID Type / Status
Subject Nancy E24594 entity
Predicate hasShortForm P43 FINISHED
Object Nance E9716 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: Nance | Statement: [Nancy, hasShortForm, Nance]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nance
Context triple: [Nancy, hasShortForm, Nance]
  • A. Nance chosen
    Nance is the middle name of John Nance Garner, the 32nd vice president of the United States under Franklin D. Roosevelt.
  • B. Nancy
    Nancy is a feminine given name of Hebrew origin meaning "grace" that became especially popular in English-speaking countries in the 20th century.
  • C. Nancy
    Nancy is a historic city in northeastern France renowned for its elegant 18th-century architecture and UNESCO-listed Place Stanislas.
  • D. Leslie
    Leslie is a small town in Fife, Scotland, situated near Glenrothes and known historically for its textile and papermaking industries.
  • E. Leslie
    Leslie is the given name of Leslie R. Groves Jr., the U.S. Army Corps of Engineers officer who directed the Manhattan Project during World War II.
  • 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_69a494060e148190abb42f971242c197 completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bccc62a88190882d8801908015a4 completed March 1, 2026, 10:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad307e887c81909f81473a2f02c2ba completed March 8, 2026, 8:17 a.m.
Created at: March 1, 2026, 7:45 p.m.