Triple

T24043138
Position Surface form Disambiguated ID Type / Status
Subject CTA Route 9 Ashland E595439 entity
Predicate hasStopOn P17789 FINISHED
Object Ashland/95th
Ashland/95th is a major Chicago Transit Authority bus stop and transfer point located near the intersection of Ashland Avenue and 95th Street on the city’s South Side.
E1622977 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: Ashland/95th | Statement: [CTA Route 9 Ashland, hasStopOn, Ashland/95th]
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: Ashland/95th
Triple: [CTA Route 9 Ashland, hasStopOn, Ashland/95th]
Generated description
Ashland/95th is a major Chicago Transit Authority bus stop and transfer point located near the intersection of Ashland Avenue and 95th Street on the city’s South Side.

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_69e288c06a908190899cad4531f32c9a completed April 17, 2026, 7:23 p.m.
NER Named-entity recognition batch_69f1d8db3b4c81908a36eace8ec136cc completed April 29, 2026, 10:09 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0fad065cbc81908c6f28db44028717 completed May 22, 2026, 1:10 a.m.
NEDg Description generation batch_6a0fadbe98a08190bcde092c36f2159a completed May 22, 2026, 1:13 a.m.
NED2 Entity disambiguation (via description) batch_6a0fae34bb948190b8f936d8f47d7c41 completed May 22, 2026, 1:15 a.m.
Created at: April 17, 2026, 9:58 p.m.