Triple

T24966196
Position Surface form Disambiguated ID Type / Status
Subject Upper Wacker Drive E624749 entity
Predicate isPartOf P10 FINISHED
Object Chicago multilevel street system
The Chicago multilevel street system is a network of stacked roadways in downtown Chicago designed to separate local, through, and service traffic on different levels to improve circulation and reduce congestion.
E1659854 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: Chicago multilevel street system | Statement: [Upper Wacker Drive, isPartOf, Chicago multilevel street system]
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: Chicago multilevel street system
Triple: [Upper Wacker Drive, isPartOf, Chicago multilevel street system]
Generated description
The Chicago multilevel street system is a network of stacked roadways in downtown Chicago designed to separate local, through, and service traffic on different levels to improve circulation and reduce congestion.

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_69e2ff24512481908e9a72315b8d0354 completed April 18, 2026, 3:48 a.m.
NER Named-entity recognition batch_69f444d7f9e4819098276f05604b2f2a completed May 1, 2026, 6:14 a.m.
NED1 Entity disambiguation (via context triple) batch_6a103355135481909306042f5dab0339 completed May 22, 2026, 10:43 a.m.
NEDg Description generation batch_6a10343efd288190884ee9ebcb1b4afb completed May 22, 2026, 10:47 a.m.
NED2 Entity disambiguation (via description) batch_6a1034fb076881908947b97895c6bbc1 completed May 22, 2026, 10:50 a.m.
Created at: April 18, 2026, 6 a.m.