Triple

T23243775
Position Surface form Disambiguated ID Type / Status
Subject Mary Esther Lee E581527 entity
Predicate placeOfDeath P21 FINISHED
Object Hanover NE NERFINISHED

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: Hanover | Statement: [Mary Esther Lee, placeOfDeath, Hanover]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hanover
Context triple: [Mary Esther Lee, placeOfDeath, Hanover]
  • A. Hanover
    Hanover is a historic city in northern Germany that served as the capital of the former Kingdom of Hanover and the ancestral seat of the British House of Hanover.
  • B. Hanover
    Hanover is a small town in South Africa, known as the birthplace of prominent trade unionist Zwelinzima Vavi.
  • C. Hanover
    Hanover is a character in the 1998 sci-fi action horror film "Deep Rising," portrayed as the ruthless leader of a group of mercenaries.
  • D. Hanover
    Hanover is a small New Hampshire town best known as the home of Dartmouth College, an Ivy League institution.
  • E. Hanover
    Hanover is a small suburban town in Plymouth County, Massachusetts, known for its residential character and local businesses south of Boston.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide. chosen

Provenance (2 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_69e24606b17c81908aba1a4911c8a8ba completed April 17, 2026, 2:39 p.m.
NER Named-entity recognition batch_69f192efd44c8190b179b4d1cb71efa5 completed April 29, 2026, 5:11 a.m.
Created at: April 17, 2026, 4:10 p.m.