Triple

T35660896
Position Surface form Disambiguated ID Type / Status
Subject United States polar icebreaking fleet E1030430 entity
Predicate componentVessel P38891 FINISHED
Object USCGC Polar Sea
USCGC Polar Sea is a United States Coast Guard heavy icebreaker designed for polar operations, including scientific research support and logistical missions in Arctic and Antarctic waters.
E2159043 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: USCGC Polar Sea | Statement: [United States polar icebreaking fleet, componentVessel, USCGC Polar Sea]
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: USCGC Polar Sea
Triple: [United States polar icebreaking fleet, componentVessel, USCGC Polar Sea]
Generated description
USCGC Polar Sea is a United States Coast Guard heavy icebreaker designed for polar operations, including scientific research support and logistical missions in Arctic and Antarctic waters.

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_69f76e09f87881909c954aaac176c34f completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69fdb19d17d481908b1758a07f9ce296 completed May 8, 2026, 9:49 a.m.
NED1 Entity disambiguation (via context triple) batch_6a38a4d26f1c8190860493ae43aa1323 completed June 22, 2026, 2:58 a.m.
NEDg Description generation batch_6a38a53e2e3481909af59554610d45be completed June 22, 2026, 3 a.m.
NED2 Entity disambiguation (via description) batch_6a38a584e79c819089ac34d732d1f189 completed June 22, 2026, 3:01 a.m.
Created at: May 3, 2026, 4:05 p.m.