Triple

T6836242
Position Surface form Disambiguated ID Type / Status
Subject Thomas M. Cooley Law School E157457 entity
Predicate locatedIn P40 FINISHED
Object Lansing, Michigan E16556 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: Lansing, Michigan | Statement: [Thomas M. Cooley Law School, locatedIn, Lansing, Michigan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lansing, Michigan
Context triple: [Thomas M. Cooley Law School, locatedIn, Lansing, Michigan]
  • A. Lansing, Michigan chosen
    Lansing, Michigan is the capital city of the U.S. state of Michigan and a historic center of automobile manufacturing and industry.
  • B. Lansing
    Lansing is a surname of English origin borne by various notable individuals, including American statesman Robert Lansing.
  • C. Lansing
    Lansing is a small village located within Tompkins County in central New York State, near the city of Ithaca.
  • D. Hancock, Michigan
    Hancock, Michigan is a small city in Michigan’s Upper Peninsula known for its rich copper-mining heritage, Finnish-American culture, and proximity to the Keweenaw Peninsula’s historic and natural attractions.
  • E. Monroe, Michigan
    Monroe, Michigan is a small city in southeastern Michigan near the western shore of Lake Erie, known for its historic downtown, industrial base, and role in the Battle of Frenchtown during the War of 1812.
  • 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_69c6882c53608190b99aebef079b23bd completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d67c1c508190ab39b8aaaaacc628 completed March 27, 2026, 7:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7617566f481908d49d3e285c4fdae completed March 28, 2026, 5:04 a.m.
Created at: March 27, 2026, 2:19 p.m.