Triple

T16380020
Position Surface form Disambiguated ID Type / Status
Subject Evan Moore E397777 entity
Predicate name P16 FINISHED
Object Evan Moore
Evan Moore is a person whose specific public background or notable achievements are not clearly identifiable from the given information.
 E1229166 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: Evan Moore | Statement: [Evan Moore, name, Evan Moore]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Evan Moore
Context triple: [Evan Moore, name, Evan Moore]
  • A. Evan Moore
    Evan Moore is an entrepreneur best known as one of the co-founders of the food delivery platform DoorDash.
  • B. Evan Martin
    Evan Martin is a software engineer known for his work on the Ninja build system and contributions to large-scale C++ development tooling.
  • C. Evan Mast
    Evan Mast is an American musician and producer best known as one half of the electronic duo Ratatat and for his production work with prominent hip-hop artists.
  • D. Evan McPherson
    Evan McPherson is an American football placekicker in the NFL, best known for his clutch postseason performances with the Cincinnati Bengals.
  • E. Evan Roe
    Evan Roe is an American actor best known for playing Jason McCord, the youngest son of the U.S. Secretary of State, on the political drama series "Madam Secretary."
  • 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: Evan Moore
Triple: [Evan Moore, name, Evan Moore]
Generated description
Evan Moore is a person whose specific public background or notable achievements are not clearly identifiable from the given information.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Evan Moore
Target entity description: Evan Moore is a person whose specific public background or notable achievements are not clearly identifiable from the given information.
  • A. Evan Moore
    Evan Moore is an entrepreneur best known as one of the co-founders of the food delivery platform DoorDash.
  • B. Evan Martin
    Evan Martin is a software engineer known for his work on the Ninja build system and contributions to large-scale C++ development tooling.
  • C. Evan Mast
    Evan Mast is an American musician and producer best known as one half of the electronic duo Ratatat and for his production work with prominent hip-hop artists.
  • D. Evan McPherson
    Evan McPherson is an American football placekicker in the NFL, best known for his clutch postseason performances with the Cincinnati Bengals.
  • E. Evan Roe
    Evan Roe is an American actor best known for playing Jason McCord, the youngest son of the U.S. Secretary of State, on the political drama series "Madam Secretary."
  • 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_69d87f2880b48190ae1a9673a3bbef80 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e319db5b648190a8fca23518a1fb39 completed April 18, 2026, 5:42 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0091855ab48190a14ad7df9cd806ad completed May 10, 2026, 2:09 p.m.
NEDg Description generation batch_6a00926f74548190b9719afb5eb10a14 completed May 10, 2026, 2:13 p.m.
NED2 Entity disambiguation (via description) batch_6a0092fabb3c819092193bf5d8b93616 completed May 10, 2026, 2:15 p.m.
Created at: April 10, 2026, 5:08 a.m.