Triple

T31150298
Position Surface form Disambiguated ID Type / Status
Subject Rufus King Park E794052 entity
Predicate adjacentTo P224 FINISHED
Object 153rd Street
153rd Street is a local street in Queens, New York City, running through the Jamaica neighborhood near Rufus King Park.
E1978428 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: 153rd Street | Statement: [Rufus King Park, adjacentTo, 153rd Street]
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: 153rd Street
Triple: [Rufus King Park, adjacentTo, 153rd Street]
Generated description
153rd Street is a local street in Queens, New York City, running through the Jamaica neighborhood near Rufus King Park.

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_69f224d41bb48190a5621cd1485e3a30 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f697eeb64881908cbc442cace01633 completed May 3, 2026, 12:33 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2d9d2cbd208190b05b30cbf199ce78 completed June 13, 2026, 6:10 p.m.
NEDg Description generation batch_6a2da10bb4d08190a3b400b15ef7e410 completed June 13, 2026, 6:27 p.m.
NED2 Entity disambiguation (via description) batch_6a2da307849081908102ed2d21f01f03 completed June 13, 2026, 6:35 p.m.
Created at: April 29, 2026, 9:06 p.m.