Triple

T20205816
Position Surface form Disambiguated ID Type / Status
Subject Union Pacific Big Boy class locomotives E493346 entity
Predicate designer P184 FINISHED
Object Otto Jabelmann
Otto Jabelmann was an American locomotive engineer best known for leading the design of Union Pacific’s massive and iconic Big Boy class steam locomotives.
E2068677 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: Otto Jabelmann | Statement: [Union Pacific Big Boy class locomotives, designer, Otto Jabelmann]
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: Otto Jabelmann
Triple: [Union Pacific Big Boy class locomotives, designer, Otto Jabelmann]
Generated description
Otto Jabelmann was an American locomotive engineer best known for leading the design of Union Pacific’s massive and iconic Big Boy class steam locomotives.

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_69da6269614c8190bb40475d9d477358 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e66d922ebc8190ae012da8ceba74dd completed April 20, 2026, 6:16 p.m.
NED1 Entity disambiguation (via context triple) batch_6a366e7289948190935c9a4dd719ae64 completed June 20, 2026, 10:41 a.m.
NEDg Description generation batch_6a366f1569bc8190bfdf0b57f76fc6a7 completed June 20, 2026, 10:44 a.m.
NED2 Entity disambiguation (via description) batch_6a366fedb3588190bb44217ac4b2d3e8 completed June 20, 2026, 10:48 a.m.
Created at: April 11, 2026, 11:38 p.m.