Triple

T25807780
Position Surface form Disambiguated ID Type / Status
Subject North Bank Line E650018 entity
Predicate runsBetween P15632 FINISHED
Object Spokane and Seattle
Spokane and Seattle are two major cities in Washington State, with Spokane in the eastern part near the Idaho border and Seattle on the western Puget Sound coast.
E1707821 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: Spokane and Seattle | Statement: [North Bank Line, runsBetween, Spokane and Seattle]
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: Spokane and Seattle
Triple: [North Bank Line, runsBetween, Spokane and Seattle]
Generated description
Spokane and Seattle are two major cities in Washington State, with Spokane in the eastern part near the Idaho border and Seattle on the western Puget Sound coast.

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_69e7ab35d264819095367f7e80c983ff completed April 21, 2026, 4:52 p.m.
NER Named-entity recognition batch_69f600c18a14819081b5914dd3b0f9cf completed May 2, 2026, 1:48 p.m.
NED1 Entity disambiguation (via context triple) batch_6a111af197f48190924ab9b9130d8dee completed May 23, 2026, 3:11 a.m.
NEDg Description generation batch_6a111c6d51308190a083d3a650e57c94 completed May 23, 2026, 3:18 a.m.
NED2 Entity disambiguation (via description) batch_6a111dca95888190bbe8b18c7603a5ba completed May 23, 2026, 3:23 a.m.
Created at: April 22, 2026, 7:05 a.m.