Triple

T34253565
Position Surface form Disambiguated ID Type / Status
Subject 93rd Division (Provisional) E878810 entity
Predicate hasComponentUnit P11709 FINISHED
Object 371st Infantry Regiment
The 371st Infantry Regiment was an African American infantry unit of the U.S. Army that notably served with distinction in World War I as part of the segregated 93rd Division.
E2106767 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: 371st Infantry Regiment | Statement: [93rd Division (Provisional), hasComponentUnit, 371st Infantry Regiment]
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: 371st Infantry Regiment
Triple: [93rd Division (Provisional), hasComponentUnit, 371st Infantry Regiment]
Generated description
The 371st Infantry Regiment was an African American infantry unit of the U.S. Army that notably served with distinction in World War I as part of the segregated 93rd Division.

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_69f349b421cc8190b4b4655e1d612548 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f712a424e48190be8513664fb82e5a completed May 3, 2026, 9:17 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3748d3931881909ed5d98b2b79694d completed June 21, 2026, 2:13 a.m.
NEDg Description generation batch_6a374cac1584819082c730899f12aba0 completed June 21, 2026, 2:30 a.m.
NED2 Entity disambiguation (via description) batch_6a374d01cc6c8190b2558c80783f7175 completed June 21, 2026, 2:31 a.m.
Created at: May 1, 2026, 1:56 a.m.