Triple

T17877125
Position Surface form Disambiguated ID Type / Status
Subject Town of Darien, New York E446983 entity
Predicate hasMajorRoad P385 FINISHED
Object New York State Route 77
New York State Route 77 is a north–south state highway in western New York that connects rural communities and provides access to attractions such as Darien Lake.
E2026319 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 York State Route 77 | Statement: [Town of Darien, New York, hasMajorRoad, New York State Route 77]
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 York State Route 77
Triple: [Town of Darien, New York, hasMajorRoad, New York State Route 77]
Generated description
New York State Route 77 is a north–south state highway in western New York that connects rural communities and provides access to attractions such as Darien Lake.

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_69d8b9f4c22c819093c2680434472894 completed April 10, 2026, 8:51 a.m.
NER Named-entity recognition batch_69e49aa6d24081908212e10d07c85a2b completed April 19, 2026, 9:04 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34bcc9386081909ca60354943f9fab completed June 19, 2026, 3:51 a.m.
NEDg Description generation batch_6a34bf0c10fc8190984532e2cfdbe4af completed June 19, 2026, 4:01 a.m.
NED2 Entity disambiguation (via description) batch_6a34bfc147708190bc07234245da06d5 completed June 19, 2026, 4:04 a.m.
Created at: April 10, 2026, 10:18 a.m.