Triple

T13444222
Position Surface form Disambiguated ID Type / Status
Subject Paul Halmos E320438 entity
Predicate familyName P18 FINISHED
Object Halmos
Halmos is the surname of Paul Halmos, a prominent 20th-century mathematician known for his contributions to probability theory, functional analysis, and mathematical exposition.
 E1041772 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: Halmos | Statement: [Paul Halmos, familyName, Halmos]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Halmos
Context triple: [Paul Halmos, familyName, Halmos]
  • A. Hoel
    Hoel is a given name and surname of Breton and Welsh origin, historically borne by several medieval rulers and later used in various European cultures.
  • B. Hausdorff
    Hausdorff is a topological separation property requiring that any two distinct points in a space can be enclosed in disjoint open sets.
  • C. Rudin
    Rudin is a surname most prominently associated with American film and theater producer Scott Rudin.
  • D. Rudin
    "Rudin" is a novel by Ivan Turgenev that portrays an eloquent but ineffectual intellectual whose inability to act reflects the dilemmas of the Russian intelligentsia in the mid-19th century.
  • E. Billingsley
    Billingsley is an English-origin surname borne by various notable individuals in fields such as entertainment, sports, and academia.
  • 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: Halmos
Triple: [Paul Halmos, familyName, Halmos]
Generated description
Halmos is the surname of Paul Halmos, a prominent 20th-century mathematician known for his contributions to probability theory, functional analysis, and mathematical exposition.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Halmos
Target entity description: Halmos is the surname of Paul Halmos, a prominent 20th-century mathematician known for his contributions to probability theory, functional analysis, and mathematical exposition.
  • A. Hoel
    Hoel is a given name and surname of Breton and Welsh origin, historically borne by several medieval rulers and later used in various European cultures.
  • B. Hausdorff
    Hausdorff is a topological separation property requiring that any two distinct points in a space can be enclosed in disjoint open sets.
  • C. Rudin
    Rudin is a surname most prominently associated with American film and theater producer Scott Rudin.
  • D. Rudin
    "Rudin" is a novel by Ivan Turgenev that portrays an eloquent but ineffectual intellectual whose inability to act reflects the dilemmas of the Russian intelligentsia in the mid-19th century.
  • E. Billingsley
    Billingsley is an English-origin surname borne by various notable individuals in fields such as entertainment, sports, and academia.
  • 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_69d80761e6cc8190a90c844589998ecc completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbaee881888190811ddf01bc699864 completed April 12, 2026, 2:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69f739965ef081909e85881ce805bbb5 completed May 3, 2026, 12:03 p.m.
NEDg Description generation batch_69f740e536d48190af369b38aa42438d completed May 3, 2026, 12:34 p.m.
NED2 Entity disambiguation (via description) batch_69f741b72d08819087808bf9bcffa0a1 completed May 3, 2026, 12:38 p.m.
Created at: April 9, 2026, 9:40 p.m.