Triple

T36262409
Position Surface form Disambiguated ID Type / Status
Subject The Wabash Cannonball E892125 entity
Predicate isAbout P380 FINISHED
Object Wabash Cannonball train
The Wabash Cannonball train is a legendary American passenger train immortalized in folk song and railroad lore as a symbol of early 20th-century rail travel.
E2176107 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: Wabash Cannonball train | Statement: [The Wabash Cannonball, isAbout, Wabash Cannonball train]
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: Wabash Cannonball train
Triple: [The Wabash Cannonball, isAbout, Wabash Cannonball train]
Generated description
The Wabash Cannonball train is a legendary American passenger train immortalized in folk song and railroad lore as a symbol of early 20th-century rail travel.

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_69f76e4699188190af045b11a840ce31 completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7b6239a40819096d61246367b612c completed May 3, 2026, 8:54 p.m.
NED1 Entity disambiguation (via context triple) batch_6a396e0a94308190ad57c17802e2b133 completed June 22, 2026, 5:16 p.m.
NEDg Description generation batch_6a396ed615e88190afc150b7ad4121ef completed June 22, 2026, 5:20 p.m.
NED2 Entity disambiguation (via description) batch_6a396fd681a88190a687284b93b848d1 completed June 22, 2026, 5:24 p.m.
Created at: May 3, 2026, 4:09 p.m.