Triple

T11473352
Position Surface form Disambiguated ID Type / Status
Subject Good Bones E271963 entity
Predicate setting P1957 FINISHED
Object Indianapolis, Indiana E58849 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: Indianapolis, Indiana | Statement: [Good Bones, setting, Indianapolis, Indiana]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Indianapolis, Indiana
Context triple: [Good Bones, setting, Indianapolis, Indiana]
  • A. Indianapolis chosen
    Indianapolis is the capital and most populous city of the U.S. state of Indiana, known for its major sports franchises and hosting the annual Indianapolis 500 auto race.
  • B. Columbus, Indiana
    Columbus, Indiana is a small Midwestern city renowned for its exceptional collection of modernist architecture and public art.
  • C. Fort Wayne, Indiana
    Fort Wayne, Indiana is a major city in northeastern Indiana known as a regional economic, cultural, and manufacturing hub.
  • D. South Bend, Indiana
    South Bend, Indiana is a mid-sized city in northern Indiana known for its manufacturing heritage, proximity to the University of Notre Dame, and role as an economic and cultural hub of the region.
  • E. Lafayette, Indiana
    Lafayette, Indiana is a mid-sized city in northwestern Indiana known as a regional economic and educational hub near Purdue University.
  • 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_69d6aae0c8d881908a5a360c0be3242e completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8294b3f388190a587c358313f7260 completed April 9, 2026, 10:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69e6042507c4819096afc2839fda186d completed April 20, 2026, 10:47 a.m.
Created at: April 8, 2026, 9:35 p.m.