Triple

T23292975
Position Surface form Disambiguated ID Type / Status
Subject Connecticut Route 66 E590083 entity
Predicate hasJunctionWith P1018 FINISHED
Object Connecticut Route 17
Connecticut Route 17 is a state highway in Connecticut that runs generally north–south, connecting the Middletown area to Glastonbury and other communities while intersecting several major routes.
E1804233 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: Connecticut Route 17 | Statement: [Connecticut Route 66, hasJunctionWith, Connecticut Route 17]
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: Connecticut Route 17
Triple: [Connecticut Route 66, hasJunctionWith, Connecticut Route 17]
Generated description
Connecticut Route 17 is a state highway in Connecticut that runs generally north–south, connecting the Middletown area to Glastonbury and other communities while intersecting several major routes.

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_69e25d1af9d88190a0b9b5e8fa608618 completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f196ccd9b481909ab5d3504640025e completed April 29, 2026, 5:27 a.m.
NED1 Entity disambiguation (via context triple) batch_6a15d76a3c6c819094455069fdee5547 completed May 26, 2026, 5:24 p.m.
NEDg Description generation batch_6a15d82ac0fc819082a575f3f11f25da completed May 26, 2026, 5:28 p.m.
NED2 Entity disambiguation (via description) batch_6a15d8e229e88190aaf00c672b1bf5da completed May 26, 2026, 5:31 p.m.
Created at: April 17, 2026, 5:02 p.m.