Triple

T4577694
Position Surface form Disambiguated ID Type / Status
Subject Northern Pennsylvania E123178 entity
Predicate contains P35 FINISHED
Object Warren
Warren is a small city in northern Pennsylvania known for its historic downtown and location along the Allegheny River.
 E453531 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: [Northern Pennsylvania, contains, Warren]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Warren
Context triple: [Northern Pennsylvania, contains, 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. Leland
    Leland is a masculine given name of English origin, historically associated with figures such as American industrialist and Stanford University founder Leland Stanford.
  • 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: [Northern Pennsylvania, contains, Warren]
Generated description
Warren is a small city in northern Pennsylvania known for its historic downtown and location along the Allegheny River.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Warren
Target entity description: Warren is a small city in northern Pennsylvania known for its historic downtown and location along the Allegheny River.
  • 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. Leland
    Leland is a masculine given name of English origin, historically associated with figures such as American industrialist and Stanford University founder Leland Stanford.
  • F. None of above. chosen

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_69bd46466c7081909d07f36be2d08804 completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd58e153908190ac8f578e03aecdfc completed March 20, 2026, 2:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdd3ee510481909d481b157bd0b2bd completed March 20, 2026, 11:10 p.m.
NEDg Description generation batch_69bdd5a85488819092a4a7cc4f58a425 completed March 20, 2026, 11:18 p.m.
NED2 Entity disambiguation (via description) batch_69bdd63370088190adca99373f83374f completed March 20, 2026, 11:20 p.m.
Created at: March 20, 2026, 1:10 p.m.