Triple

T17715573
Position Surface form Disambiguated ID Type / Status
Subject Franklin Gardner E442188 entity
Predicate familyName P18 FINISHED
Object Gardner 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: Gardner | Statement: [Franklin Gardner, familyName, Gardner]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gardner
Context triple: [Franklin 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 (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_69d8b9ec79688190b86bdcef85a7b3aa completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e47480955481908fa0d3d34aaedd48 completed April 19, 2026, 6:21 a.m.
Created at: April 10, 2026, 10:06 a.m.