Triple

T20058343
Position Surface form Disambiguated ID Type / Status
Subject M2 motorway E499399 entity
Predicate passesNear P416 FINISHED
Object Rochester
Rochester is a historic city in Kent, England, known for its Norman castle, cathedral, and connections to Charles Dickens.
 E116344 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: Rochester | Statement: [M2 motorway, passesNear, Rochester]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Rochester
Context triple: [M2 motorway, passesNear, Rochester]
  • A. Rochester
    Rochester is a rural town in northern Victoria, Australia, known for its agricultural community and location near the Campaspe River.
  • B. Rochester
    Rochester is a major city in western New York State known historically for its role in industry, photography, and social reform movements.
  • C. Rochester
    Rochester is a small borough in western Pennsylvania situated along the Ohio River in Beaver County.
  • D. Rochester
    Rochester is a small historic town in southeastern Massachusetts known for its rural character and New England charm.
  • E. Rochester
    Rochester is a major city in southeastern Minnesota known for being the home of the world-renowned Mayo Clinic.
  • 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: Rochester
Triple: [M2 motorway, passesNear, Rochester]
Generated description
Rochester is a historic city in Kent, England, known for its Norman castle, cathedral, and connections to Charles Dickens.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Rochester
Target entity description: Rochester is a historic city in Kent, England, known for its Norman castle, cathedral, and connections to Charles Dickens.
  • A. Rochester chosen
    Rochester is a historic cathedral city and former market town in Kent, England, known for its Norman castle, Romanesque cathedral, and strong associations with the novelist Charles Dickens.
  • B. Rochester
    Rochester is a major city in western New York State known historically for its role in industry, photography, and social reform movements.
  • C. Rochester
    Rochester is a small historic town in southeastern Massachusetts known for its rural character and New England charm.
  • D. Rochester
    Rochester is a major city in southeastern Minnesota known for being the home of the world-renowned Mayo Clinic.
  • E. Rochester
    Rochester is a small village located in Lorain County in the U.S. state of Ohio.
  • 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_69da6276bcf48190aabbf279192a5fb4 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e6637325908190aefc0e27e2ed5750 completed April 20, 2026, 5:33 p.m.
NED1 Entity disambiguation (via context triple) batch_6a082dc8db54819092ced7c6a506afaa completed May 16, 2026, 8:41 a.m.
NEDg Description generation batch_6a082e93a1e88190bac5daae12ece9f2 completed May 16, 2026, 8:45 a.m.
NED2 Entity disambiguation (via description) batch_6a082f334dd481908edb6ea3ae07e0a7 completed May 16, 2026, 8:47 a.m.
Created at: April 11, 2026, 3:38 p.m.