Triple

T9615734
Position Surface form Disambiguated ID Type / Status
Subject Essex County Park System E232213 entity
Predicate hasPart P35 FINISHED
Object Riverbank Park
Riverbank Park is a historic public park in Newark, New Jersey, known for its riverside green space, recreational facilities, and role as a community gathering place.
E1343552 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: Riverbank Park | Statement: [Essex County Park System, hasPart, Riverbank Park]
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: Riverbank Park
Triple: [Essex County Park System, hasPart, Riverbank Park]
Generated description
Riverbank Park is a historic public park in Newark, New Jersey, known for its riverside green space, recreational facilities, and role as a community gathering place.

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_69ca84867bb88190b4b57dd5a56d5691 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9aabb6b88190b53547db885e0129 completed April 1, 2026, 10:22 p.m.
NED1 Entity disambiguation (via context triple) batch_6a5cb0497bb4819084c48d3dcf77f31c completed July 19, 2026, 11:08 a.m.
NEDg Description generation batch_6a5cb0dba4fc8190a98986b1c9970e77 completed July 19, 2026, 11:11 a.m.
NED2 Entity disambiguation (via description) batch_6a5cb19ca7d881909ea4d6fd309d5d21 completed July 19, 2026, 11:14 a.m.
Created at: March 30, 2026, 8:09 p.m.