Triple

T4424019
Position Surface form Disambiguated ID Type / Status
Subject Woodlawn Cemetery (Detroit) E95166 entity
Predicate notableBurial P196 FINISHED
Object Albert Cobo E400993 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: Albert Cobo | Statement: [Woodlawn Cemetery (Detroit), notableBurial, Albert Cobo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Albert Cobo
Context triple: [Woodlawn Cemetery (Detroit), notableBurial, Albert Cobo]
  • A. Albert Cobo chosen
    Albert Cobo was a mid-20th-century mayor of Detroit known for his role in the city’s postwar urban development and fiscal management.
  • B. Nacio Herb Brown
    Nacio Herb Brown was an American composer best known for his popular film and stage songs of the 1920s and 1930s, many written with lyricist Arthur Freed for MGM musicals.
  • C. Kim Boggs
    Kim Boggs is the compassionate teenage girl who becomes Edward’s love interest and moral anchor in the fantasy film "Edward Scissorhands."
  • D. Rance Cleaveland
    Rance Cleaveland is a computer scientist known for his work in formal methods and model checking, particularly in the verification of concurrent and distributed systems.
  • E. Elmer Layden
    Elmer Layden was an American football player, coach, and executive best known as one of Notre Dame’s famed “Four Horsemen” and later as the first commissioner of the National Football League.
  • 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_69b3453a36908190b95a79a297ca083c completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b3554ca5208190ba2661616dcf071c completed March 13, 2026, 12:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69b5f62f7eb88190a02669845126e790 completed March 14, 2026, 11:58 p.m.
Created at: March 12, 2026, 11:30 p.m.