Triple

T29465256
Position Surface form Disambiguated ID Type / Status
Subject 505 CCW E747358 entity
Predicate subordinateUnit P258 FINISHED
Object 84th Radar Evaluation Squadron
The 84th Radar Evaluation Squadron is a United States Air Force unit responsible for testing, evaluating, and optimizing radar and air defense systems to ensure effective airspace surveillance and control.
E1868418 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: 84th Radar Evaluation Squadron | Statement: [505 CCW, subordinateUnit, 84th Radar Evaluation Squadron]
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: 84th Radar Evaluation Squadron
Triple: [505 CCW, subordinateUnit, 84th Radar Evaluation Squadron]
Generated description
The 84th Radar Evaluation Squadron is a United States Air Force unit responsible for testing, evaluating, and optimizing radar and air defense systems to ensure effective airspace surveillance and control.

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_69f0bd4125f88190b56104591351619c completed April 28, 2026, 1:59 p.m.
NER Named-entity recognition batch_69f66ba6316c8190a84523b9bd642e9a completed May 2, 2026, 9:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a25f115d4788190b7604baf3d9f84ec completed June 7, 2026, 10:30 p.m.
NEDg Description generation batch_6a25f6362f6081909a04ef3fbd5bb67f completed June 7, 2026, 10:52 p.m.
NED2 Entity disambiguation (via description) batch_6a25fa9d98d08190aef6fb0a1779f501 completed June 7, 2026, 11:11 p.m.
Created at: April 28, 2026, 3:52 p.m.