Triple

T21979446
Position Surface form Disambiguated ID Type / Status
Subject Detroit–Warren–Dearborn Metropolitan Statistical Area E542797 entity
Predicate containsCity P294 FINISHED
Object Warren
Warren is a major suburban city in Michigan, known as the largest city in Macomb County and a key part of the Detroit metropolitan area.
 E135327 NE FINISHED

How this triple was built (4 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: Warren | Statement: [Detroit–Warren–Dearborn Metropolitan Statistical Area, containsCity, Warren]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Warren
Context triple: [Detroit–Warren–Dearborn Metropolitan Statistical Area, containsCity, Warren]
  • A. Warren
    Warren is the given name of Warren Buffett, the renowned American investor and longtime CEO of Berkshire Hathaway.
  • B. Warren
    Warren is a common English surname borne by numerous notable figures in politics, law, entertainment, and other fields.
  • C. Warren
    Warren is a rural town in the Orana region of New South Wales, Australia, known for its agriculture and proximity to the Macquarie River.
  • D. Warren
    Warren is a central character in Robert Frost's narrative poem "The Death of the Hired Man," depicted as a New England farmer whose conflicted sense of duty and forgiveness shapes the story's moral tension.
  • E. Warren
    Warren is a mid-sized industrial city in northeastern Ohio known historically for its role in the steel and automotive industries.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Warren
Triple: [Detroit–Warren–Dearborn Metropolitan Statistical Area, containsCity, Warren]
Generated description
Warren is a major suburban city in Michigan, known as the largest city in Macomb County and a key part of the Detroit metropolitan area.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Warren
Target entity description: Warren is a major suburban city in Michigan, known as the largest city in Macomb County and a key part of the Detroit metropolitan area.
  • A. Warren chosen
    Warren is a large suburban city in southeast Michigan known for its extensive automotive and defense manufacturing industries.
  • B. Warren
    Warren is a mid-sized industrial city in northeastern Ohio known historically for its role in the steel and automotive industries.
  • C. Warren
    Warren is a small city in northern Pennsylvania known for its historic downtown and location along the Allegheny River.
  • D. Warren
    Warren is a small unincorporated community located within Waushara County in the U.S. state of Wisconsin.
  • E. Warren
    Warren is a small community that forms part of the municipality of Markstay-Warren in Ontario, Canada.
  • F. None of above.

Provenance (5 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_69e0c48070988190909db97667b9a0ac completed April 16, 2026, 11:14 a.m.
NER Named-entity recognition batch_69f1248bdd88819098bfeca550608f14 completed April 28, 2026, 9:20 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0a7369ebd48190886004cacd06c9d3 completed May 18, 2026, 2:03 a.m.
NEDg Description generation batch_6a0a7439a4448190abcb7d0c89bf9479 completed May 18, 2026, 2:06 a.m.
NED2 Entity disambiguation (via description) batch_6a0a74cd737c81909efa0eefe5eb8f52 completed May 18, 2026, 2:09 a.m.
Created at: April 16, 2026, 8:03 p.m.