Triple

T13858925
Position Surface form Disambiguated ID Type / Status
Subject Leslie Knope E333135 entity
Predicate residence P75 FINISHED
Object Pawnee, Indiana E634122 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: Pawnee, Indiana | Statement: [Leslie Knope, residence, Pawnee, Indiana]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pawnee, Indiana
Context triple: [Leslie Knope, residence, Pawnee, Indiana]
  • A. Pawnee, Indiana chosen
    Pawnee, Indiana is the fictional Midwestern town that serves as the primary setting for the television comedy series "Parks and Recreation."
  • B. Pendleton, Indiana
    Pendleton, Indiana is a small town in Madison County known for its historic downtown, Falls Park, and role as a gateway community between Indianapolis and east-central Indiana.
  • C. La Paz, Indiana
    La Paz, Indiana is a small Midwestern town located in northern Indiana within Marshall County.
  • D. Osceola, Indiana
    Osceola, Indiana is a small town in northern Indiana situated between the cities of South Bend and Elkhart.
  • E. Loogootee, Indiana
    Loogootee, Indiana is a small city in southwestern Indiana known for its tight-knit community and strong high school basketball tradition.
  • 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_69d81c5ba13c8190839315f54768acfd completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de02de38e48190b6ead95561031c32 completed April 14, 2026, 9:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69fcb649c12c819086e85d1dc49624f1 completed May 7, 2026, 3:56 p.m.
Created at: April 9, 2026, 10:14 p.m.