Triple

T33163347
Position Surface form Disambiguated ID Type / Status
Subject Newport, Vermont E848808 entity
Predicate transportation P230 FINISHED
Object Vermont Route 105
Vermont Route 105 is a state highway running across northern Vermont, connecting several communities near the Canadian border and serving as a key east–west transportation corridor in the region.
 E2080957 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 105 | Statement: [Newport, Vermont, transportation, Vermont Route 105]
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 105
Triple: [Newport, Vermont, transportation, Vermont Route 105]
Generated description
Vermont Route 105 is a state highway running across northern Vermont, connecting several communities near the Canadian border and serving as a key east–west transportation corridor in the 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_69f3495be8808190bbf427733df08aad completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6d902f2d081909fe2d2a99ebb1ab1 completed May 3, 2026, 5:11 a.m.
NED1 Entity disambiguation (via context triple) batch_6a36ae2cb3988190812190ac37979c3d completed June 20, 2026, 3:13 p.m.
NEDg Description generation batch_6a36aef5e62c81909695813abde97094 completed June 20, 2026, 3:17 p.m.
NED2 Entity disambiguation (via description) batch_6a36afe7a9208190952f11924f15856b completed June 20, 2026, 3:21 p.m.
Created at: May 1, 2026, 1:28 a.m.