Triple

T12281896
Position Surface form Disambiguated ID Type / Status
Subject KDevelop E292733 entity
Predicate supportsBuildSystem P13398 FINISHED
Object Make
Make is a widely used build automation tool that uses Makefiles to compile and manage software projects by tracking dependencies and executing build commands.
 E973150 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: Make | Statement: [KDevelop, supportsBuildSystem, Make]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Make
Context triple: [KDevelop, supportsBuildSystem, Make]
  • A. Amaker
    Amaker is the surname of Tommy Amaker, an American college basketball coach and former player best known for coaching at Harvard University.
  • B. Made
    Made is a town in the Dutch province of North Brabant, known as one of the population centers within the municipality of Drimmelen.
  • C. Machen
    Machen is a surname most notably associated with J. Gresham Machen, an influential early 20th-century American Presbyterian theologian and New Testament scholar.
  • D. The Maker
    "The Maker" is a track by the electronic music producer Teatro, likely showcasing his signature atmospheric and melodic style.
  • E. Makers
    Makers is a science fiction novel by Cory Doctorow that explores a near-future maker culture, disruptive innovation, and the social and economic upheavals caused by rapid technological change.
  • 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: Make
Triple: [KDevelop, supportsBuildSystem, Make]
Generated description
Make is a widely used build automation tool that uses Makefiles to compile and manage software projects by tracking dependencies and executing build commands.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Make
Target entity description: Make is a widely used build automation tool that uses Makefiles to compile and manage software projects by tracking dependencies and executing build commands.
  • A. Amaker
    Amaker is the surname of Tommy Amaker, an American college basketball coach and former player best known for coaching at Harvard University.
  • B. Made
    Made is a town in the Dutch province of North Brabant, known as one of the population centers within the municipality of Drimmelen.
  • C. Machen
    Machen is a surname most notably associated with J. Gresham Machen, an influential early 20th-century American Presbyterian theologian and New Testament scholar.
  • D. The Maker
    "The Maker" is a track by the electronic music producer Teatro, likely showcasing his signature atmospheric and melodic style.
  • E. Makers
    Makers is a science fiction novel by Cory Doctorow that explores a near-future maker culture, disruptive innovation, and the social and economic upheavals caused by rapid technological change.
  • 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_69d6ab690ad081908c0ed3870ec82d53 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d91cf2b09c81908a11581d33f65be0 completed April 10, 2026, 3:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69f61e70dec8819098199fbb54d888c1 completed May 2, 2026, 3:55 p.m.
NEDg Description generation batch_69f61f5bc1fc8190af9d74acc307ebe1 completed May 2, 2026, 3:59 p.m.
NED2 Entity disambiguation (via description) batch_69f62041f2408190ad320fec5283abdd completed May 2, 2026, 4:03 p.m.
Created at: April 8, 2026, 9:52 p.m.