Triple

T9796870
Position Surface form Disambiguated ID Type / Status
Subject Sea, Lake, and Overland Surges from Hurricanes model E237737 entity
Predicate partOf P40 FINISHED
Object U.S. hurricane forecast and warning system
The U.S. hurricane forecast and warning system is the national framework of observational tools, computer models, and communication protocols used to predict hurricanes and issue timely alerts to protect life and property.
E821384 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: U.S. hurricane forecast and warning system | Statement: [Sea, Lake, and Overland Surges from Hurricanes model, partOf, U.S. hurricane forecast and warning system]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: U.S. hurricane forecast and warning system
Context triple: [Sea, Lake, and Overland Surges from Hurricanes model, partOf, U.S. hurricane forecast and warning system]
  • A. Hurricane and Storm Damage Risk Reduction System program
    The Hurricane and Storm Damage Risk Reduction System program is a U.S. Army Corps of Engineers initiative designed to strengthen and modernize flood and storm surge defenses in the New Orleans region following Hurricane Katrina.
  • B. Sea, Lake, and Overland Surges from Hurricanes model
    The Sea, Lake, and Overland Surges from Hurricanes (SLOSH) model is a computer simulation tool developed by the U.S. National Weather Service to estimate storm surge heights and inundation from tropical cyclones for coastal emergency planning and forecasting.
  • C. World Meteorological Organization regional warning system
    The World Meteorological Organization regional warning system is a global network of specialized centers that monitor and issue alerts for severe weather and related hazards to support international safety and disaster risk reduction.
  • D. Tropical Cyclone Warning Centers
    Tropical Cyclone Warning Centers are specialized meteorological agencies around the world responsible for monitoring, forecasting, and issuing warnings about tropical cyclones in their designated regions.
  • E. Saffir–Simpson Hurricane Wind Scale
    The Saffir–Simpson Hurricane Wind Scale is a 1-to-5 categorization system that rates hurricanes based on their sustained wind speeds and potential for property damage.
  • 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: U.S. hurricane forecast and warning system
Triple: [Sea, Lake, and Overland Surges from Hurricanes model, partOf, U.S. hurricane forecast and warning system]
Generated description
The U.S. hurricane forecast and warning system is the national framework of observational tools, computer models, and communication protocols used to predict hurricanes and issue timely alerts to protect life and property.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: U.S. hurricane forecast and warning system
Target entity description: The U.S. hurricane forecast and warning system is the national framework of observational tools, computer models, and communication protocols used to predict hurricanes and issue timely alerts to protect life and property.
  • A. Hurricane and Storm Damage Risk Reduction System program
    The Hurricane and Storm Damage Risk Reduction System program is a U.S. Army Corps of Engineers initiative designed to strengthen and modernize flood and storm surge defenses in the New Orleans region following Hurricane Katrina.
  • B. Sea, Lake, and Overland Surges from Hurricanes model
    The Sea, Lake, and Overland Surges from Hurricanes (SLOSH) model is a computer simulation tool developed by the U.S. National Weather Service to estimate storm surge heights and inundation from tropical cyclones for coastal emergency planning and forecasting.
  • C. World Meteorological Organization regional warning system
    The World Meteorological Organization regional warning system is a global network of specialized centers that monitor and issue alerts for severe weather and related hazards to support international safety and disaster risk reduction.
  • D. Tropical Cyclone Warning Centers
    Tropical Cyclone Warning Centers are specialized meteorological agencies around the world responsible for monitoring, forecasting, and issuing warnings about tropical cyclones in their designated regions.
  • E. Saffir–Simpson Hurricane Wind Scale
    The Saffir–Simpson Hurricane Wind Scale is a 1-to-5 categorization system that rates hurricanes based on their sustained wind speeds and potential for property damage.
  • 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_69ca84dc04488190b9c91193976c0960 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cda34a53548190a8cb524381fe2bf9 completed April 1, 2026, 10:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1c43fdfec8190b7115a680c79d702 completed April 5, 2026, 2:09 a.m.
NEDg Description generation batch_69d1c4d62a78819089ece2bb1f5fb66b completed April 5, 2026, 2:11 a.m.
NED2 Entity disambiguation (via description) batch_69d1c589b90481908bc0944868d648b2 completed April 5, 2026, 2:14 a.m.
Created at: March 30, 2026, 8:28 p.m.