Triple

T4445172
Position Surface form Disambiguated ID Type / Status
Subject Michigan Historical Museum E96267 entity
Predicate city P40 FINISHED
Object Lansing 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 | Statement: [Michigan Historical Museum, city, Lansing]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lansing
Context triple: [Michigan Historical Museum, city, Lansing]
  • A. Lansing
    Lansing is a surname of English origin borne by various notable individuals, including American statesman Robert Lansing.
  • B. Lansing
    Lansing is a small village located within Tompkins County in central New York State, near the city of Ithaca.
  • C. 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.
  • D. Kalamazoo
    Kalamazoo is a mid-sized city in southwestern Michigan known for its historic downtown, educational institutions like Western Michigan University, and a legacy of manufacturing and craft beer.
  • E. Saginaw
    Saginaw is a city in central Michigan known for its industrial history, location along the Saginaw River, and role as a regional economic and cultural center.
  • 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_69b345415ba481908df738e7174448ba completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b355d00c288190a4f3fec29b5d85b2 completed March 13, 2026, 12:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69b65f3b9950819085c285defda52d51 completed March 15, 2026, 7:26 a.m.
Created at: March 12, 2026, 11:32 p.m.