Triple

T27405432
Position Surface form Disambiguated ID Type / Status
Subject Northfield, New Jersey E691981 entity
Predicate hasTransportationAccess P1298 FINISHED
Object County Route 563
County Route 563 is a major county highway in southern New Jersey that connects several communities in Atlantic County and serves as an important local thoroughfare.
E1773204 NE FINISHED

How this triple was built (2 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: County Route 563 | Statement: [Northfield, New Jersey, hasTransportationAccess, County Route 563]
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: County Route 563
Triple: [Northfield, New Jersey, hasTransportationAccess, County Route 563]
Generated description
County Route 563 is a major county highway in southern New Jersey that connects several communities in Atlantic County and serves as an important local thoroughfare.

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_69ef5205fc808190ad3efc5525b8e6d6 completed April 27, 2026, 12:09 p.m.
NER Named-entity recognition batch_69f62cd580ac8190a50bfd2fc1984b07 completed May 2, 2026, 4:56 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12b23ed5048190bcf8f387ab69550e completed May 24, 2026, 8:09 a.m.
NEDg Description generation batch_6a12b4bb7f5481908290eefad23b73db completed May 24, 2026, 8:20 a.m.
NED2 Entity disambiguation (via description) batch_6a12b53828688190978b1547d0753f30 completed May 24, 2026, 8:22 a.m.
Created at: April 27, 2026, 12:30 p.m.