Triple

T13196065
Position Surface form Disambiguated ID Type / Status
Subject Chief Warrant Officer 5 E314114 entity
Predicate payGrade P7397 FINISHED
Object W-5
W-5 is the highest warrant officer pay grade in the U.S. military, reserved for the most senior and experienced warrant officers.
 E1026256 NE FINISHED

How this triple was built (4 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: W-5 | Statement: [Chief Warrant Officer 5, payGrade, W-5]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: W-5
Context triple: [Chief Warrant Officer 5, payGrade, W-5]
  • A. W-53
    The W-53 was a high-yield American thermonuclear warhead developed during the Cold War and deployed on Titan II intercontinental ballistic missiles.
  • B. W-31
    W-31 is a high-performance option package for the Oldsmobile 442 muscle car, featuring factory-upgraded engine and handling components aimed at enthusiasts.
  • C. W4
    W4 is a prominent star-forming region in the Milky Way, notable for its large ionized gas bubble and active formation of massive young stars.
  • D. W-30
    W-30 is a high-performance option package for the Oldsmobile 442 muscle car, known for enhancing power, handling, and overall track capability.
  • E. W-1
    W-1 is the entry-level warrant officer pay grade in the United States Navy, typically held by technical specialists who serve as highly skilled leaders and advisors.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: W-5
Triple: [Chief Warrant Officer 5, payGrade, W-5]
Generated description
W-5 is the highest warrant officer pay grade in the U.S. military, reserved for the most senior and experienced warrant officers.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: W-5
Target entity description: W-5 is the highest warrant officer pay grade in the U.S. military, reserved for the most senior and experienced warrant officers.
  • A. W-53
    The W-53 was a high-yield American thermonuclear warhead developed during the Cold War and deployed on Titan II intercontinental ballistic missiles.
  • B. W-31
    W-31 is a high-performance option package for the Oldsmobile 442 muscle car, featuring factory-upgraded engine and handling components aimed at enthusiasts.
  • C. W4
    W4 is a prominent star-forming region in the Milky Way, notable for its large ionized gas bubble and active formation of massive young stars.
  • D. W-30
    W-30 is a high-performance option package for the Oldsmobile 442 muscle car, known for enhancing power, handling, and overall track capability.
  • E. W-1
    W-1 is the entry-level warrant officer pay grade in the United States Navy, typically held by technical specialists who serve as highly skilled leaders and advisors.
  • F. None of above. chosen

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_69d806ae1e08819090d95bfe1538cc17 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98c626058819086f604b11af2d4eb completed April 10, 2026, 11:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6f605a48c81909373fcd9dd896b3d completed May 3, 2026, 7:15 a.m.
NEDg Description generation batch_69f6f6e10f2481909b405169dd7e5cf9 completed May 3, 2026, 7:18 a.m.
NED2 Entity disambiguation (via description) batch_69f6f73b301881909d792dfebd2e468f completed May 3, 2026, 7:20 a.m.
Created at: April 9, 2026, 9:16 p.m.