Triple

T36496894
Position Surface form Disambiguated ID Type / Status
Subject 20th Special Operations Squadron E899213 entity
Predicate motto P42 FINISHED
Object Semper Flexibilis
Semper Flexibilis is the Latin motto of the U.S. Air Force's 20th Special Operations Squadron, reflecting its emphasis on adaptability and versatility in special operations missions.
E2185963 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: Semper Flexibilis | Statement: [20th Special Operations Squadron, motto, Semper Flexibilis]
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: Semper Flexibilis
Triple: [20th Special Operations Squadron, motto, Semper Flexibilis]
Generated description
Semper Flexibilis is the Latin motto of the U.S. Air Force's 20th Special Operations Squadron, reflecting its emphasis on adaptability and versatility in special operations missions.

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_69f76e5ad4588190bdbce60c52fbb785 completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7c1bff1088190ae868a3222e53506 completed May 3, 2026, 9:44 p.m.
NED1 Entity disambiguation (via context triple) batch_6a39cfe6adc88190b9c10945a07c606b completed June 23, 2026, 12:14 a.m.
NEDg Description generation batch_6a39d3c95e848190b627e2014527b3a9 completed June 23, 2026, 12:31 a.m.
NED2 Entity disambiguation (via description) batch_6a39d448857481908b32ad6a81040ff3 completed June 23, 2026, 12:33 a.m.
Created at: May 3, 2026, 4:10 p.m.