Triple

T14968732
Position Surface form Disambiguated ID Type / Status
Subject New York State Route 59 E373259 entity
Predicate connectsTo P845 FINISHED
Object New York State Route 306
New York State Route 306 is a north–south state highway in Rockland County, New York, running through suburban communities such as Monsey and Wesley Hills.
E1646120 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 306 | Statement: [New York State Route 59, connectsTo, New York State Route 306]
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 306
Triple: [New York State Route 59, connectsTo, New York State Route 306]
Generated description
New York State Route 306 is a north–south state highway in Rockland County, New York, running through suburban communities such as Monsey and Wesley Hills.

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_69d85ccbbcd48190acb56e7cf104d8ad completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded6e44cb0819096e09f8026ef8174 completed April 15, 2026, 12:08 a.m.
NED1 Entity disambiguation (via context triple) batch_6a100fc486c48190b42494cf2a047264 completed May 22, 2026, 8:11 a.m.
NEDg Description generation batch_6a10136871588190b4e4b4618ab7a400 completed May 22, 2026, 8:27 a.m.
NED2 Entity disambiguation (via description) batch_6a10141161b08190b471a7882a4d8aa0 completed May 22, 2026, 8:30 a.m.
Created at: April 10, 2026, 2:48 a.m.