Triple

T6238438
Position Surface form Disambiguated ID Type / Status
Subject Youngstown–Warren–Boardman metropolitan area E139533 entity
Predicate containsCity P294 FINISHED
Object Warren
Warren is a small industrial city in northeastern Ohio, historically tied to steel manufacturing and part of the Mahoning Valley region.
 E577554 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: [Youngstown–Warren–Boardman metropolitan area, containsCity, Warren]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Warren
Context triple: [Youngstown–Warren–Boardman metropolitan 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 large suburban city in southeast Michigan known for its extensive automotive and defense manufacturing industries.
  • D. 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.
  • E. 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.
  • 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: [Youngstown–Warren–Boardman metropolitan area, containsCity, Warren]
Generated description
Warren is a small industrial city in northeastern Ohio, historically tied to steel manufacturing and part of the Mahoning Valley region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Warren
Target entity description: Warren is a small industrial city in northeastern Ohio, historically tied to steel manufacturing and part of the Mahoning Valley region.
  • A. Warren chosen
    Warren is a mid-sized industrial city in northeastern Ohio known historically for its role in the steel and automotive industries.
  • B. Warren
    Warren is a small city in northern Pennsylvania known for its historic downtown and location along the Allegheny River.
  • C. Warren
    Warren is a large suburban city in southeast Michigan known for its extensive automotive and defense manufacturing industries.
  • D. 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.
  • E. Warren
    Warren is a common English surname borne by numerous notable figures in politics, law, entertainment, and other fields.
  • 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_69c008b0e7ac8190808a59573ee646f3 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c0630373088190a9d4b1f7e442c129 completed March 22, 2026, 9:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69c5190e0a6481909e5372334a851770 completed March 26, 2026, 11:31 a.m.
NEDg Description generation batch_69c51b947088819089242ce511e2c639 completed March 26, 2026, 11:42 a.m.
NED2 Entity disambiguation (via description) batch_69c5843fd33c8190be48371960cfbfbb completed March 26, 2026, 7:08 p.m.
Created at: March 22, 2026, 4:23 p.m.