Triple

T27110585
Position Surface form Disambiguated ID Type / Status
Subject Diversey Parkway E686698 entity
Predicate hasNearbyTransit P5822 FINISHED
Object Diversey CTA Red Line station
Diversey CTA Red Line station is a Chicago 'L' rapid transit stop in the Lincoln Park area, serving the Red Line along with connections to nearby Brown and Purple Line trains.
E1765476 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: Diversey CTA Red Line station | Statement: [Diversey Parkway, hasNearbyTransit, Diversey CTA Red Line 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: Diversey CTA Red Line station
Triple: [Diversey Parkway, hasNearbyTransit, Diversey CTA Red Line station]
Generated description
Diversey CTA Red Line station is a Chicago 'L' rapid transit stop in the Lincoln Park area, serving the Red Line along with connections to nearby Brown and Purple Line trains.

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_69ef148accd48190b6ed6e13a15f2a4f completed April 27, 2026, 7:47 a.m.
NER Named-entity recognition batch_69f6240111c08190a863d9786d36af1d completed May 2, 2026, 4:19 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12625a6b808190b18d2212a514c9d1 completed May 24, 2026, 2:28 a.m.
NEDg Description generation batch_6a126d04c0ac8190a0be232512d7baad completed May 24, 2026, 3:14 a.m.
NED2 Entity disambiguation (via description) batch_6a126e5956f8819087415e8b62a2e1f5 completed May 24, 2026, 3:19 a.m.
Created at: April 27, 2026, 8:53 a.m.