Triple

T11984607
Position Surface form Disambiguated ID Type / Status
Subject Grandpa Joe E285245 entity
Predicate spouse P13 FINISHED
Object Grandma Josephine E958271 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: Grandma Josephine | Statement: [Grandpa Joe, spouse, Grandma Josephine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Grandma Josephine
Context triple: [Grandpa Joe, spouse, Grandma Josephine]
  • A. Grandma Josephine chosen
    Grandma Josephine is one of Charlie Bucket’s elderly, bedridden grandmothers in Roald Dahl’s novel "Charlie and the Chocolate Factory."
  • B. Josephine (grandmother)
    Josephine is the grandmother of Omar Little, a key character in the television series "The Wire."
  • C. Grandmother Spaulding
    Grandmother Spaulding is a warm, wise, and nostalgic figure in Ray Bradbury’s novel "Dandelion Wine," embodying the comforts and traditions of small-town family life.
  • D. Nannie
    Nannie is a feminine given name, often used as a diminutive or variant of names like Nancy or Anne.
  • E. Grandma
    Grandma is a key supporting character in the 2020 dark fantasy film "The Witches," serving as the wise and protective guardian who helps her grandson confront a secret society of child-hating witches.
  • 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_69d6ab44a77c8190a652f4b27164e4ef completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d903973c848190aac871d6dfecc74b completed April 10, 2026, 2:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69f48aa73458819097a69b371350743c completed May 1, 2026, 11:12 a.m.
Created at: April 8, 2026, 9:46 p.m.