Triple

T27374440
Position Surface form Disambiguated ID Type / Status
Subject North Meridian Street E691021 entity
Predicate hasNameElement P3097 FINISHED
Object Meridian Street
Meridian Street is a major thoroughfare name used in various U.S. cities, often serving as a central north–south route or reference line in local street grids.
E2286041 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: Meridian Street | Statement: [North Meridian Street, hasNameElement, Meridian Street]
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: Meridian Street
Triple: [North Meridian Street, hasNameElement, Meridian Street]
Generated description
Meridian Street is a major thoroughfare name used in various U.S. cities, often serving as a central north–south route or reference line in local street grids.

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_69ef52022538819081f873d0c84a6dd6 completed April 27, 2026, 12:09 p.m.
NER Named-entity recognition batch_69f62c649f908190807c02d3f65942a4 completed May 2, 2026, 4:55 p.m.
NED1 Entity disambiguation (via context triple) batch_6a4644959d6c8190b64e5fefce44a91e completed July 2, 2026, 10:59 a.m.
NEDg Description generation batch_6a46487f02108190915df96faf5b7cf3 completed July 2, 2026, 11:16 a.m.
NED2 Entity disambiguation (via description) batch_6a4648da447881909c056bf07e8b8175 completed July 2, 2026, 11:17 a.m.
Created at: April 27, 2026, 12:20 p.m.