Triple

T30882633
Position Surface form Disambiguated ID Type / Status
Subject 1st U.S. Cavalry Regiment E786660 entity
Predicate hasComponent P35 FINISHED
Object 1st Squadron, 1st Cavalry Regiment
The 1st Squadron, 1st Cavalry Regiment is a historic U.S. Army cavalry unit that has served in various reconnaissance and armored roles across multiple major conflicts.
E1935949 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 Squadron, 1st Cavalry Regiment | Statement: [1st U.S. Cavalry Regiment, hasComponent, 1st Squadron, 1st Cavalry 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: 1st Squadron, 1st Cavalry Regiment
Triple: [1st U.S. Cavalry Regiment, hasComponent, 1st Squadron, 1st Cavalry Regiment]
Generated description
The 1st Squadron, 1st Cavalry Regiment is a historic U.S. Army cavalry unit that has served in various reconnaissance and armored roles across multiple major conflicts.

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_69f224bae17c8190bb3a6a28e3d019df completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f6920402e481909686774789e914ef completed May 3, 2026, 12:08 a.m.
NED1 Entity disambiguation (via context triple) batch_6a28c7e394148190879e7289b948c3ac completed June 10, 2026, 2:11 a.m.
NEDg Description generation batch_6a28cb64769081908e49db0f66024852 completed June 10, 2026, 2:26 a.m.
NED2 Entity disambiguation (via description) batch_6a28cc7003c081908373122f59284b68 completed June 10, 2026, 2:31 a.m.
Created at: April 29, 2026, 8:48 p.m.