Triple

T14058952
Position Surface form Disambiguated ID Type / Status
Subject Town of Chester, New York E338292 entity
Predicate hasName P744 FINISHED
Object Chester
Chester is a small town in Orange County, New York, known for its rural character and historic village center.
 E1078637 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: Chester | Statement: [Town of Chester, New York, hasName, Chester]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Chester
Context triple: [Town of Chester, New York, hasName, Chester]
  • A. Chester
    Chester is the given name of Chester W. Nimitz, the prominent U.S. Navy fleet admiral who played a leading role in the Pacific theater during World War II.
  • B. Chester
    Chester is a historic walled city in northwest England known for its Roman heritage, medieval architecture, and distinctive two-tiered shopping galleries called the Rows.
  • C. Chester
    Chester is a historic walled city in northwest England renowned for its Roman heritage, medieval architecture, and well-preserved city walls.
  • D. Chester
    Chester is a historic walled city in northwest England, renowned for its well-preserved Roman and medieval architecture.
  • E. Chester
    Chester is a historic city in northwest England known for its Roman walls, medieval architecture, and distinctive black-and-white timbered buildings.
  • 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: Chester
Triple: [Town of Chester, New York, hasName, Chester]
Generated description
Chester is a small town in Orange County, New York, known for its rural character and historic village center.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Chester
Target entity description: Chester is a small town in Orange County, New York, known for its rural character and historic village center.
  • A. Chester
    Chester is a small, historically industrial city in southeastern Pennsylvania that lies just southwest of Philadelphia along the Delaware River.
  • B. Chester
    Chester is a historic city in northwest England known for its Roman walls, medieval architecture, and distinctive black-and-white timbered buildings.
  • C. Chester
    Chester is a historic walled city in northwest England known for its Roman heritage, medieval architecture, and distinctive two-tiered shopping galleries called the Rows.
  • D. Chester
    Chester is a historic walled city in northwest England, renowned for its well-preserved Roman and medieval architecture.
  • E. Chester
    Chester is a historic walled city in northwest England renowned for its Roman heritage, medieval architecture, and well-preserved city walls.
  • 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_69d81c67ba6c819091935650dfb3b895 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de5686f51c81908c33143ecbaae83d completed April 14, 2026, 3 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcb662c37c8190a629278a97060080 completed May 7, 2026, 3:57 p.m.
NEDg Description generation batch_69fcc99fca8c8190bbcafba5bacfdfda completed May 7, 2026, 5:19 p.m.
NED2 Entity disambiguation (via description) batch_69fcca3a375c819092b3f67612d2ec0c completed May 7, 2026, 5:22 p.m.
Created at: April 9, 2026, 10:20 p.m.