Triple

T2258793
Position Surface form Disambiguated ID Type / Status
Subject Hamilton County, Ohio E49788 entity
Predicate contains P35 FINISHED
Object Reading, Ohio
Reading, Ohio is a small suburban city located just north of Cincinnati in Hamilton County.
E270154 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: Reading, Ohio | Statement: [Hamilton County, Ohio, contains, Reading, Ohio]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Reading, Ohio
Context triple: [Hamilton County, Ohio, contains, Reading, Ohio]
  • A. Reynoldsburg, Ohio
    Reynoldsburg, Ohio is a suburban city near Columbus best known as the longtime home of Victoria’s Secret’s corporate headquarters.
  • B. Norwalk, Ohio
    Norwalk, Ohio is a small city in northern Ohio that serves as the county seat of Huron County and a regional hub for the surrounding rural communities.
  • C. Montgomery, Ohio
    Montgomery, Ohio is a suburban city in Hamilton County near Cincinnati, known for its historic charm, affluent residential character, and well-regarded schools.
  • D. Springfield, Ohio
    Springfield, Ohio is a mid-sized city in western Ohio known historically for manufacturing and as the seat of Clark County.
  • E. Norwood, Ohio
    Norwood, Ohio is a small independent city surrounded by Cincinnati that was historically known for its major General Motors automobile assembly plant.
  • 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: Reading, Ohio
Triple: [Hamilton County, Ohio, contains, Reading, Ohio]
Generated description
Reading, Ohio is a small suburban city located just north of Cincinnati in Hamilton County.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Reading, Ohio
Target entity description: Reading, Ohio is a small suburban city located just north of Cincinnati in Hamilton County.
  • A. Reynoldsburg, Ohio
    Reynoldsburg, Ohio is a suburban city near Columbus best known as the longtime home of Victoria’s Secret’s corporate headquarters.
  • B. Norwalk, Ohio
    Norwalk, Ohio is a small city in northern Ohio that serves as the county seat of Huron County and a regional hub for the surrounding rural communities.
  • C. Montgomery, Ohio
    Montgomery, Ohio is a suburban city in Hamilton County near Cincinnati, known for its historic charm, affluent residential character, and well-regarded schools.
  • D. Springfield, Ohio
    Springfield, Ohio is a mid-sized city in western Ohio known historically for manufacturing and as the seat of Clark County.
  • E. Norwood, Ohio
    Norwood, Ohio is a small independent city surrounded by Cincinnati that was historically known for its major General Motors automobile assembly plant.
  • 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_69a88aaa9250819095e127d0d77e8a32 completed March 4, 2026, 7:40 p.m.
NER Named-entity recognition batch_69abc15ad06c8190b6d0babc17015787 completed March 7, 2026, 6:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69af17695e6481908bb7e4848a5ffc09 completed March 9, 2026, 6:54 p.m.
NEDg Description generation batch_69af1a0749148190bb23911440a8ee1e completed March 9, 2026, 7:05 p.m.
NED2 Entity disambiguation (via description) batch_69af1a6c684481909458c26e18f0cf3a completed March 9, 2026, 7:07 p.m.
Created at: March 4, 2026, 7:48 p.m.