Triple

T22744709
Position Surface form Disambiguated ID Type / Status
Subject Danny and the Miracles E562515 entity
Predicate city P40 FINISHED
Object Lawrence, Kansas 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: Lawrence, Kansas | Statement: [Danny and the Miracles, city, Lawrence, Kansas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lawrence, Kansas
Context triple: [Danny and the Miracles, city, Lawrence, Kansas]
  • A. Lawrence, Kansas chosen
    Lawrence, Kansas is a vibrant college town in northeastern Kansas known for the University of Kansas, its historic downtown, and a strong arts and music scene.
  • B. Newton, Kansas
    Newton, Kansas is a small city in south-central Kansas known historically as a railroad hub and gateway to the American West.
  • C. Wichita, Kansas
    Wichita, Kansas is the largest city in the state of Kansas, known as a major center for the U.S. aircraft industry and situated in south-central Kansas along the Arkansas River.
  • D. Lakin, Kansas
    Lakin, Kansas is a small city in southwestern Kansas that serves as the administrative and economic center of Kearny County.
  • E. Topeka, Kansas
    Topeka, Kansas is the capital city of the U.S. state of Kansas, historically significant as the community at the center of the landmark school desegregation case Brown v. Board of Education.
  • 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_69e245513a5c81908d5cb471b4fc429d completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f1797590f08190a784f73fcd27b101 completed April 29, 2026, 3:22 a.m.
Created at: April 17, 2026, 3:23 p.m.