Triple

T30526351
Position Surface form Disambiguated ID Type / Status
Subject Cambridge, Vermont E776854 entity
Predicate hasMajorRoute P385 FINISHED
Object Vermont Route 104
Vermont Route 104 is a state highway in northern Vermont that connects several communities in Franklin and Lamoille counties, serving as an important regional transportation corridor.
 E2010202 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: Vermont Route 104 | Statement: [Cambridge, Vermont, hasMajorRoute, Vermont Route 104]
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: Vermont Route 104
Triple: [Cambridge, Vermont, hasMajorRoute, Vermont Route 104]
Generated description
Vermont Route 104 is a state highway in northern Vermont that connects several communities in Franklin and Lamoille counties, serving as an important regional transportation corridor.

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_69f2249c11508190ae7e955755ccfb01 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f6880f92d48190a6ac8547c34ef7d3 completed May 2, 2026, 11:26 p.m.
NED1 Entity disambiguation (via context triple) batch_6a34702900308190ad4468e4ceff59f4 completed June 18, 2026, 10:24 p.m.
NEDg Description generation batch_6a3470d2101c8190bc7c6a246420a06a completed June 18, 2026, 10:27 p.m.
NED2 Entity disambiguation (via description) batch_6a34714da9c481908ef8aec2f25b5024 completed June 18, 2026, 10:29 p.m.
Created at: April 29, 2026, 8:17 p.m.