Triple

T38111957
Position Surface form Disambiguated ID Type / Status
Subject New York lawyer moves to rural farming community E951678 entity
Predicate commonTrope P68123 FINISHED
Object big-city professional in the country LITERAL 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: big-city professional in the country | Statement: [New York lawyer moves to rural farming community, commonTrope, big-city professional in the country]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: commonTrope
Context triple: [New York lawyer moves to rural farming community, commonTrope, big-city professional in the country]
  • A. usedAsTrope chosen
    Indicates that something functions as a recurring narrative device, motif, or cliché within a story or set of stories.
  • B. inspiredTrope
    Indicates that one trope serves as the creative or conceptual inspiration for another trope.
  • C. subvertsTrope
    Indicates that one entity challenges, undermines, or reverses the expected pattern or convention represented by a particular trope.
  • D. narrativeMotif
    Indicates a recurring thematic element, pattern, or situation that appears across one or more narratives and helps structure or convey their underlying meanings.
  • E. tvtropesPage
    Indicates that one entity is the TVTropes webpage corresponding to, describing, or cataloging the tropes of another entity.
  • F. None of above.

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_69f76f065ed08190bdfb1b6d817f5b39 completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_69ff6fba1a5c8190a660279a6271d785 completed May 9, 2026, 5:32 p.m.
PD Predicate disambiguation batch_69ff6f59388c8190a7d6ab7bc7705bc0 completed May 9, 2026, 5:31 p.m.
Created at: May 3, 2026, 4:21 p.m.