Triple

T318853
Position Surface form Disambiguated ID Type / Status
Subject Storm Prediction Center E7768 entity
Predicate locatedInCity P40 FINISHED
Object Norman
Norman is a city in central Oklahoma known for its strong ties to meteorology and atmospheric research, including hosting major national weather institutions.
 E41178 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: Norman | Statement: [Storm Prediction Center, locatedInCity, Norman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Norman
Context triple: [Storm Prediction Center, locatedInCity, Norman]
  • A. Norman
    Norman is a masculine given name of English origin that became widely used in the English-speaking world.
  • B. Bladon
    Bladon is a village in Oxfordshire, England, best known as the burial place of Sir Winston Churchill.
  • C. Geoffrey
    Geoffrey is a masculine given name of English origin, famously borne by pioneering computer scientist and AI researcher Geoffrey Hinton.
  • D. Graham
    Graham is the surname of Elizabeth Arden, the pioneering Canadian-American businesswoman who founded the iconic Elizabeth Arden cosmetics empire.
  • E. Lawrence
    Lawrence is a historic mill city in northeastern Massachusetts that developed as a major textile manufacturing center along the Merrimack River.
  • 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: Norman
Triple: [Storm Prediction Center, locatedInCity, Norman]
Generated description
Norman is a city in central Oklahoma known for its strong ties to meteorology and atmospheric research, including hosting major national weather institutions.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Norman
Target entity description: Norman is a city in central Oklahoma known for its strong ties to meteorology and atmospheric research, including hosting major national weather institutions.
  • A. Norman
    Norman is a masculine given name of English origin that became widely used in the English-speaking world.
  • B. Bladon
    Bladon is a village in Oxfordshire, England, best known as the burial place of Sir Winston Churchill.
  • C. Geoffrey
    Geoffrey is a masculine given name of English origin, famously borne by pioneering computer scientist and AI researcher Geoffrey Hinton.
  • D. Graham
    Graham is the surname of Elizabeth Arden, the pioneering Canadian-American businesswoman who founded the iconic Elizabeth Arden cosmetics empire.
  • E. Lawrence
    Lawrence is a historic mill city in northeastern Massachusetts that developed as a major textile manufacturing center along the Merrimack River.
  • 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_69a2e7e7af7881908890039d6be4e9b8 completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2ea7edbc48190b9031bd1af48f72a completed Feb. 28, 2026, 1:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69a3c8ba3304819099db7b60f2c83c8b completed March 1, 2026, 5:03 a.m.
NEDg Description generation batch_69a3c93ce2308190b2df5c939691a2ce completed March 1, 2026, 5:06 a.m.
NED2 Entity disambiguation (via description) batch_69a3ca020b7081909b54e311c173ef21 completed March 1, 2026, 5:09 a.m.
Created at: Feb. 28, 2026, 1:08 p.m.