Triple

T38473395
Position Surface form Disambiguated ID Type / Status
Subject Route 24 (New Jersey) E915479 entity
Predicate nextRoute P18011 FINISHED
Object New Jersey Route 25
New Jersey Route 25 was a former state highway that largely followed the route of today’s U.S. Route 1 between Jersey City and New Brunswick before being renumbered and decommissioned in the mid-20th century.
E2291337 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: New Jersey Route 25 | Statement: [Route 24 (New Jersey), nextRoute, New Jersey Route 25]
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: New Jersey Route 25
Triple: [Route 24 (New Jersey), nextRoute, New Jersey Route 25]
Generated description
New Jersey Route 25 was a former state highway that largely followed the route of today’s U.S. Route 1 between Jersey City and New Brunswick before being renumbered and decommissioned in the mid-20th century.

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_69f76e8ff5cc8190a88803369183845e completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69fcd20082e081908a0367fef58d6bbf completed May 7, 2026, 5:55 p.m.
NED1 Entity disambiguation (via context triple) batch_6a5c4919d4a08190a7bb8ff08dbcb4a2 completed July 19, 2026, 3:48 a.m.
NEDg Description generation batch_6a5c49ead6748190bffce60b24716acb completed July 19, 2026, 3:52 a.m.
NED2 Entity disambiguation (via description) batch_6a5c4aa384e88190bf48e076738c0b07 completed July 19, 2026, 3:55 a.m.
Created at: May 3, 2026, 4:31 p.m.