Triple

T6461361
Position Surface form Disambiguated ID Type / Status
Subject Netherlands Cancer Institute E142128 entity
Predicate shortName P43 FINISHED
Object NKI-AVL
NKI-AVL is a leading Dutch comprehensive cancer center and research institute renowned for its advanced oncology care and pioneering cancer research.
 E594286 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: NKI-AVL | Statement: [Netherlands Cancer Institute, shortName, NKI-AVL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: NKI-AVL
Context triple: [Netherlands Cancer Institute, shortName, NKI-AVL]
  • A. NIPH
    NIPH is the commonly used abbreviation for the Norwegian Institute of Public Health, Norway’s national public health research and advisory institution.
  • B. NIA
    NIA is India’s premier federal counter-terrorism and national security investigation agency.
  • C. NIA
    NIA is the ICAO airline designator assigned to Nile Air, a private Egyptian airline based in Cairo.
  • D. NIA
    NIA is a U.S. federal research institute within the National Institutes of Health that focuses on understanding aging and age-related diseases, including Alzheimer’s disease.
  • E. NINR
    NINR is a U.S. National Institutes of Health institute that supports and conducts research to improve health and healthcare through nursing science.
  • 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: NKI-AVL
Triple: [Netherlands Cancer Institute, shortName, NKI-AVL]
Generated description
NKI-AVL is a leading Dutch comprehensive cancer center and research institute renowned for its advanced oncology care and pioneering cancer research.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: NKI-AVL
Target entity description: NKI-AVL is a leading Dutch comprehensive cancer center and research institute renowned for its advanced oncology care and pioneering cancer research.
  • A. NIPH
    NIPH is the commonly used abbreviation for the Norwegian Institute of Public Health, Norway’s national public health research and advisory institution.
  • B. NIA
    NIA is India’s premier federal counter-terrorism and national security investigation agency.
  • C. NIA
    NIA is the ICAO airline designator assigned to Nile Air, a private Egyptian airline based in Cairo.
  • D. NIA
    NIA is a U.S. federal research institute within the National Institutes of Health that focuses on understanding aging and age-related diseases, including Alzheimer’s disease.
  • E. NINR
    NINR is a U.S. National Institutes of Health institute that supports and conducts research to improve health and healthcare through nursing science.
  • 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_69c008d2f91c8190a8178767a35e08fc completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c069f683248190a58beb60f009eafb completed March 22, 2026, 10:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69c64be4e6888190a685f447e9950163 completed March 27, 2026, 9:20 a.m.
NEDg Description generation batch_69c64e4413f481908561a86bc9a9b0b2 completed March 27, 2026, 9:30 a.m.
NED2 Entity disambiguation (via description) batch_69c64ec0d40881908fda2e994f0f6ed5 completed March 27, 2026, 9:32 a.m.
Created at: March 22, 2026, 4:49 p.m.