Triple

T14960927
Position Surface form Disambiguated ID Type / Status
Subject Elizabeth Bonforte Gardner E373060 entity
Predicate familyName P18 FINISHED
Object Gardner E39619 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: Gardner | Statement: [Elizabeth Bonforte Gardner, familyName, Gardner]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gardner
Context triple: [Elizabeth Bonforte Gardner, familyName, Gardner]
  • A. Gardner chosen
    Gardner is a common English surname borne by numerous notable individuals across fields such as literature, science, and the arts.
  • B. Gardner James
    Gardner James was an American film actor active during the silent and early sound eras, known for supporting roles in adventure and drama films.
  • C. Gardner Earl
    Gardner Earl was an individual significant enough to have the Gardner Earl Memorial Chapel and Crematorium named in his honor, likely reflecting his prominence or contributions to the local community.
  • D. Gideon Gartner
    Gideon Gartner was an influential technology analyst and entrepreneur best known for founding the global research and advisory firm Gartner Inc.
  • E. Orson
    Orson is a masculine given name most famously associated with the American filmmaker and actor Orson Welles.
  • 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_69d85cca979481908747d2a81eba1cea completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded6cece6881908cd8c8fe41583bee completed April 15, 2026, 12:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe8bdd27808190b52bdbf5da5b01d6 completed May 9, 2026, 1:20 a.m.
Created at: April 10, 2026, 2:40 a.m.