Triple

T962580
Position Surface form Disambiguated ID Type / Status
Subject Erwin E20767 entity
Predicate cognate P2527 FINISHED
Object Irwin
Irwin is a masculine given name and surname of English origin, historically associated with various notable figures in fields such as entertainment, science, and politics.
 E113130 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: Irwin | Statement: [Erwin, cognate, Irwin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Irwin
Context triple: [Erwin, cognate, Irwin]
  • A. Milhous
    Milhous is the distinctive middle name of Richard Nixon, the 37th president of the United States.
  • B. Wydler
    Wydler is a surname most notably associated with American politician John W. Wydler, who served as a U.S. Representative from New York.
  • C. Noatak
    Noatak is a remote Inupiat village in northwestern Alaska situated along the Noatak River above the Arctic Circle.
  • D. Chevak
    Chevak is a distinct dialect of the Central Alaskan Yup’ik language spoken primarily in the village of Chevak in western Alaska.
  • E. Erwin
    Erwin is a masculine given name of German origin, historically associated with figures such as the World War II field marshal Erwin Rommel.
  • 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: Irwin
Triple: [Erwin, cognate, Irwin]
Generated description
Irwin is a masculine given name and surname of English origin, historically associated with various notable figures in fields such as entertainment, science, and politics.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Irwin
Target entity description: Irwin is a masculine given name and surname of English origin, historically associated with various notable figures in fields such as entertainment, science, and politics.
  • A. Milhous
    Milhous is the distinctive middle name of Richard Nixon, the 37th president of the United States.
  • B. Wydler
    Wydler is a surname most notably associated with American politician John W. Wydler, who served as a U.S. Representative from New York.
  • C. Noatak
    Noatak is a remote Inupiat village in northwestern Alaska situated along the Noatak River above the Arctic Circle.
  • D. Chevak
    Chevak is a distinct dialect of the Central Alaskan Yup’ik language spoken primarily in the village of Chevak in western Alaska.
  • E. Erwin
    Erwin is a masculine given name of German origin, historically associated with figures such as the World War II field marshal Erwin Rommel.
  • 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_69a493b21f2881908132dcf45dcd2f36 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b415ac688190bbcef455935a3116 completed March 1, 2026, 9:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac11a6107481909b152291a73958d3 completed March 7, 2026, 11:53 a.m.
NEDg Description generation batch_69ac12c5978481909be2d6e1ce85acd5 completed March 7, 2026, 11:57 a.m.
NED2 Entity disambiguation (via description) batch_69ac132f09448190b5f789f90328f81f completed March 7, 2026, 11:59 a.m.
Created at: March 1, 2026, 7:40 p.m.