Triple

T24212598
Position Surface form Disambiguated ID Type / Status
Subject East Troy Electric Railroad E600593 entity
Predicate terminus P388 FINISHED
Object East Troy depot
East Troy depot is a historic train station in East Troy, Wisconsin, that serves as the main boarding point and museum hub for the heritage East Troy Electric Railroad.
E1623729 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: East Troy depot | Statement: [East Troy Electric Railroad, terminus, East Troy depot]
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: East Troy depot
Triple: [East Troy Electric Railroad, terminus, East Troy depot]
Generated description
East Troy depot is a historic train station in East Troy, Wisconsin, that serves as the main boarding point and museum hub for the heritage East Troy Electric Railroad.

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_69e2953344c48190875730c7d52112a0 completed April 17, 2026, 8:16 p.m.
NER Named-entity recognition batch_69f2820401bc81909ae1837b41c85526 completed April 29, 2026, 10:11 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0fbd1de230819097f6d540b46efc75 completed May 22, 2026, 2:19 a.m.
NEDg Description generation batch_6a0fbe09c6e4819093b71509780fcec0 completed May 22, 2026, 2:23 a.m.
NED2 Entity disambiguation (via description) batch_6a0fbed0cbc48190963e3764a8481cbf completed May 22, 2026, 2:26 a.m.
Created at: April 17, 2026, 11:55 p.m.