Triple

T34907191
Position Surface form Disambiguated ID Type / Status
Subject Interstate MAX E1006760 entity
Predicate hasStation P35 FINISHED
Object North Prescott Street station
North Prescott Street station is a light rail stop on Portland, Oregon’s MAX Yellow Line serving the Interstate Avenue corridor.
 E2117795 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: North Prescott Street station | Statement: [Interstate MAX, hasStation, North Prescott Street station]
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: North Prescott Street station
Triple: [Interstate MAX, hasStation, North Prescott Street station]
Generated description
North Prescott Street station is a light rail stop on Portland, Oregon’s MAX Yellow Line serving the Interstate Avenue 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_69f76dc1b4a081909b4c6e4d8ec0aa2d completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f781eccb8c81909b8a1a050532de3c completed May 3, 2026, 5:12 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3786edcd0481909c6f15746c66538e completed June 21, 2026, 6:38 a.m.
NEDg Description generation batch_6a379ec2fdc08190bc9613d71f1386ec completed June 21, 2026, 8:20 a.m.
NED2 Entity disambiguation (via description) batch_6a37a06f04f88190a4cc9917c5b42aec completed June 21, 2026, 8:27 a.m.
Created at: May 3, 2026, 4 p.m.