Triple

T3543570
Position Surface form Disambiguated ID Type / Status
Subject CTA Blue Line E74942 entity
Predicate hasStation P35 FINISHED
Object Addison
Addison is a Chicago Transit Authority 'L' station on the Blue Line serving the city's Northwest Side.
 E367320 NE FINISHED

How this triple was built (4 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: Addison | Statement: [CTA Blue Line, hasStation, Addison]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Addison
Context triple: [CTA Blue Line, hasStation, Addison]
  • A. Addison
    Addison is a small, business-focused town in the Dallas–Fort Worth metropolitan area known for its dense concentration of restaurants, corporate offices, and frequent special events.
  • B. Blaine
    Blaine is a small coastal city in northwestern Washington State, located near the Canadian border.
  • C. Ashton
    Ashton is a masculine given name of English origin that has become well known through figures such as actor and entrepreneur Ashton Kutcher.
  • D. Ashton
    Ashton is a small village in the town of Cumberland in Providence County, Rhode Island, known for its historic mill district along the Blackstone River.
  • E. Addison Richards
    Addison Richards was an American character actor known for his prolific work in film and early television during the 1930s–1950s.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Addison
Triple: [CTA Blue Line, hasStation, Addison]
Generated description
Addison is a Chicago Transit Authority 'L' station on the Blue Line serving the city's Northwest Side.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Addison
Target entity description: Addison is a Chicago Transit Authority 'L' station on the Blue Line serving the city's Northwest Side.
  • A. Addison
    Addison is a small, business-focused town in the Dallas–Fort Worth metropolitan area known for its dense concentration of restaurants, corporate offices, and frequent special events.
  • B. Blaine
    Blaine is a small coastal city in northwestern Washington State, located near the Canadian border.
  • C. Ashton
    Ashton is a masculine given name of English origin that has become well known through figures such as actor and entrepreneur Ashton Kutcher.
  • D. Ashton
    Ashton is a small village in the town of Cumberland in Providence County, Rhode Island, known for its historic mill district along the Blackstone River.
  • E. Addison Richards
    Addison Richards was an American character actor known for his prolific work in film and early television during the 1930s–1950s.
  • F. None of above. chosen

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_69ad85d274cc8190ab59c97298a1cfbf completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adbf752dd481909226044ffe595338 completed March 8, 2026, 6:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69b38bdd0cb4819086119b54c2708850 completed March 13, 2026, 4 a.m.
NEDg Description generation batch_69b38cb6a2188190b68f4903144a0e51 completed March 13, 2026, 4:04 a.m.
NED2 Entity disambiguation (via description) batch_69b39062a10c8190bc227c02cf4f3ab1 completed March 13, 2026, 4:19 a.m.
Created at: March 8, 2026, 3:20 p.m.