Triple

T768076
Position Surface form Disambiguated ID Type / Status
Subject IEEE conferences E16217 entity
Predicate example P1259 FINISHED
Object IEEE International Conference on Data Mining
The IEEE International Conference on Data Mining is a leading annual research conference that focuses on advances in data mining, machine learning, and knowledge discovery in databases.
E91280 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: IEEE International Conference on Data Mining | Statement: [IEEE conferences, example, IEEE International Conference on Data Mining]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: IEEE International Conference on Data Mining
Context triple: [IEEE conferences, example, IEEE International Conference on Data Mining]
  • A. ACM Transactions on Knowledge Discovery from Data
    ACM Transactions on Knowledge Discovery from Data is a peer-reviewed scholarly journal published by the Association for Computing Machinery that focuses on research in data mining, knowledge discovery, and related areas of data science and machine learning.
  • B. SIGKDD
    SIGKDD is the ACM Special Interest Group on Knowledge Discovery and Data Mining, best known for its flagship KDD conference and contributions to data mining and machine learning research.
  • C. ACM Transactions on Data Science
    ACM Transactions on Data Science is a peer-reviewed scholarly journal published by the Association for Computing Machinery that focuses on research in data science, including theory, methods, and applications.
  • D. ACM International Conference on Web Search and Data Mining
    The ACM International Conference on Web Search and Data Mining (WSDM) is a leading annual computer science research conference focusing on web search, data mining, and related areas of information retrieval and machine learning.
  • E. ACM International Conference on Web Intelligence
    The ACM International Conference on Web Intelligence is a leading research conference focused on the theory and applications of artificial intelligence, data mining, and knowledge discovery on the web and related online systems.
  • 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: IEEE International Conference on Data Mining
Triple: [IEEE conferences, example, IEEE International Conference on Data Mining]
Generated description
The IEEE International Conference on Data Mining is a leading annual research conference that focuses on advances in data mining, machine learning, and knowledge discovery in databases.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: IEEE International Conference on Data Mining
Target entity description: The IEEE International Conference on Data Mining is a leading annual research conference that focuses on advances in data mining, machine learning, and knowledge discovery in databases.
  • A. ACM Transactions on Knowledge Discovery from Data
    ACM Transactions on Knowledge Discovery from Data is a peer-reviewed scholarly journal published by the Association for Computing Machinery that focuses on research in data mining, knowledge discovery, and related areas of data science and machine learning.
  • B. SIGKDD
    SIGKDD is the ACM Special Interest Group on Knowledge Discovery and Data Mining, best known for its flagship KDD conference and contributions to data mining and machine learning research.
  • C. ACM Transactions on Data Science
    ACM Transactions on Data Science is a peer-reviewed scholarly journal published by the Association for Computing Machinery that focuses on research in data science, including theory, methods, and applications.
  • D. ACM International Conference on Web Search and Data Mining
    The ACM International Conference on Web Search and Data Mining (WSDM) is a leading annual computer science research conference focusing on web search, data mining, and related areas of information retrieval and machine learning.
  • E. ACM International Conference on Web Intelligence
    The ACM International Conference on Web Intelligence is a leading research conference focused on the theory and applications of artificial intelligence, data mining, and knowledge discovery on the web and related online systems.
  • 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_69a49369a0848190af883934cee3db4c completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a701e584819095905cf74d33e11c completed March 1, 2026, 8:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69a66678f7ac819095eafccf44c6588e completed March 3, 2026, 4:41 a.m.
NEDg Description generation batch_69a6698255d4819095df00abfe896eac completed March 3, 2026, 4:54 a.m.
NED2 Entity disambiguation (via description) batch_69a66a495cf08190b3a2e2002c089634 completed March 3, 2026, 4:57 a.m.
Created at: March 1, 2026, 7:37 p.m.