Triple

T27195723
Position Surface form Disambiguated ID Type / Status
Subject Town of Ulster, New York E683591 entity
Predicate contains P35 FINISHED
Object Lincoln Park, New York
Lincoln Park, New York is a small hamlet and census-designated place in Ulster County, situated near the city of Kingston in the Hudson Valley region.
E1763197 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: Lincoln Park, New York | Statement: [Town of Ulster, New York, contains, Lincoln Park, New York]
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: Lincoln Park, New York
Triple: [Town of Ulster, New York, contains, Lincoln Park, New York]
Generated description
Lincoln Park, New York is a small hamlet and census-designated place in Ulster County, situated near the city of Kingston in the Hudson Valley region.

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_69eefad1fd5c8190a4a46ea6afe58bfa completed April 27, 2026, 5:57 a.m.
NER Named-entity recognition batch_69f625af81808190af840a2eab1aff15 completed May 2, 2026, 4:26 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1262686f648190bbfc032ea320605a completed May 24, 2026, 2:28 a.m.
NEDg Description generation batch_6a1265fbfe448190ac0ef932b76e7fad completed May 24, 2026, 2:44 a.m.
NED2 Entity disambiguation (via description) batch_6a1266dd3b748190a06a76a7587eff99 completed May 24, 2026, 2:47 a.m.
Created at: April 27, 2026, 9:34 a.m.