Triple

T26568741
Position Surface form Disambiguated ID Type / Status
Subject County Route 507 (Paramus Road / Oradell Avenue) E666762 entity
Predicate alsoKnownAs P39 FINISHED
Object Oradell Avenue
Oradell Avenue is a major local thoroughfare in Bergen County, New Jersey, serving residential and commercial areas and forming part of the county highway network.
E1790993 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: Oradell Avenue | Statement: [County Route 507 (Paramus Road / Oradell Avenue), alsoKnownAs, Oradell Avenue]
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: Oradell Avenue
Triple: [County Route 507 (Paramus Road / Oradell Avenue), alsoKnownAs, Oradell Avenue]
Generated description
Oradell Avenue is a major local thoroughfare in Bergen County, New Jersey, serving residential and commercial areas and forming part of the county highway network.

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_69ee9cfa21c081909e4e36e087debfc6 completed April 26, 2026, 11:17 p.m.
NER Named-entity recognition batch_69f614a1bc9481908b25759bd74dca2f completed May 2, 2026, 3:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12f6f6397481908b093e6e28341a88 completed May 24, 2026, 1:02 p.m.
NEDg Description generation batch_6a12f79fed1c81908af492a3fd35f82d completed May 24, 2026, 1:05 p.m.
NED2 Entity disambiguation (via description) batch_6a12fb9bdbe881909c9f79d153f151a3 completed May 24, 2026, 1:22 p.m.
Created at: April 27, 2026, 1:56 a.m.