Triple

T24545274
Position Surface form Disambiguated ID Type / Status
Subject Studebaker V8 engine E607204 entity
Predicate designedBy P184 FINISHED
Object Studebaker engineering department
The Studebaker engineering department was the in-house technical team of the Studebaker Corporation responsible for designing and developing the company’s automotive powertrains and other key vehicle systems.
 E1638255 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: Studebaker engineering department | Statement: [Studebaker V8 engine, designedBy, Studebaker engineering department]
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: Studebaker engineering department
Triple: [Studebaker V8 engine, designedBy, Studebaker engineering department]
Generated description
The Studebaker engineering department was the in-house technical team of the Studebaker Corporation responsible for designing and developing the company’s automotive powertrains and other key vehicle systems.

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_69e2c4c9bf94819082d05da6f5c29907 completed April 17, 2026, 11:39 p.m.
NER Named-entity recognition batch_69f2a8c84c648190bcc7edc0ac859cb0 completed April 30, 2026, 12:56 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0feea8d17c8190912b4efee020af73 completed May 22, 2026, 5:50 a.m.
NEDg Description generation batch_6a0fef6feb088190870b41df1edb338e completed May 22, 2026, 5:53 a.m.
NED2 Entity disambiguation (via description) batch_6a0ff097dd8881908bb83d84a6581ef7 completed May 22, 2026, 5:58 a.m.
Created at: April 18, 2026, 2:26 a.m.