Triple

T28731582
Position Surface form Disambiguated ID Type / Status
Subject Henry Hopkins Sibley E730673 entity
Predicate servedIn P253 FINISHED
Object 1st Dragoons
The 1st Dragoons was a U.S. Army mounted regiment active in the 19th century that served on the American frontier and later became part of the regular cavalry forces.
E1834553 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: 1st Dragoons | Statement: [Henry Hopkins Sibley, servedIn, 1st Dragoons]
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: 1st Dragoons
Triple: [Henry Hopkins Sibley, servedIn, 1st Dragoons]
Generated description
The 1st Dragoons was a U.S. Army mounted regiment active in the 19th century that served on the American frontier and later became part of the regular cavalry forces.

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_69f043eae0908190b28ce314686247d7 completed April 28, 2026, 5:21 a.m.
NER Named-entity recognition batch_69f657680a108190a4de62c3fb6a8800 completed May 2, 2026, 7:58 p.m.
NED1 Entity disambiguation (via context triple) batch_6a24a251030c81909adf606976e2dc8b completed June 6, 2026, 10:42 p.m.
NEDg Description generation batch_6a24ad2f2df48190a415e325d30321e3 completed June 6, 2026, 11:28 p.m.
NED2 Entity disambiguation (via description) batch_6a24b0e3a5cc81909d6133e7e33af0e6 completed June 6, 2026, 11:44 p.m.
Created at: April 28, 2026, 5:58 a.m.