Triple

T10162363
Position Surface form Disambiguated ID Type / Status
Subject The Scientific Basis E233920 entity
Predicate hasEditor P1954 FINISHED
Object X. Dai
X. Dai is an editor known for contributing to the scientific work "The Scientific Basis."
E845586 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: X. Dai | Statement: [The Scientific Basis, hasEditor, X. Dai]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: X. Dai
Context triple: [The Scientific Basis, hasEditor, X. Dai]
  • A. Xiaodong Chen
    Xiaodong Chen is a prominent materials scientist and nanotechnology researcher who serves as editor-in-chief of the journal ACS Nano.
  • B. Xindong Wu
    Xindong Wu is a prominent computer scientist known for his influential contributions to data mining and knowledge discovery research.
  • C. Xing Li
    Xing Li is a computer networking expert known for co-authoring IETF standards, including RFC 6145 on IPv4/IPv6 translation mechanisms.
  • D. Xing Li
    Xing Li is the creator and original developer of FanFiction.net, one of the largest and earliest online archives for user-written fan fiction.
  • E. Geling Yan
    Geling Yan is a Chinese-American novelist and screenwriter known for her emotionally powerful works that often explore the human impact of war, political upheaval, and social change in modern Chinese history.
  • 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: X. Dai
Triple: [The Scientific Basis, hasEditor, X. Dai]
Generated description
X. Dai is an editor known for contributing to the scientific work "The Scientific Basis."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: X. Dai
Target entity description: X. Dai is an editor known for contributing to the scientific work "The Scientific Basis."
  • A. Xiaodong Chen
    Xiaodong Chen is a prominent materials scientist and nanotechnology researcher who serves as editor-in-chief of the journal ACS Nano.
  • B. Xindong Wu
    Xindong Wu is a prominent computer scientist known for his influential contributions to data mining and knowledge discovery research.
  • C. Xing Li
    Xing Li is a computer networking expert known for co-authoring IETF standards, including RFC 6145 on IPv4/IPv6 translation mechanisms.
  • D. Xing Li
    Xing Li is the creator and original developer of FanFiction.net, one of the largest and earliest online archives for user-written fan fiction.
  • E. Geling Yan
    Geling Yan is a Chinese-American novelist and screenwriter known for her emotionally powerful works that often explore the human impact of war, political upheaval, and social change in modern Chinese history.
  • 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_69ca848e80748190b91d1e04d35512c7 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cdec5b5194819095645e9174897b0f completed April 2, 2026, 4:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69d300cc37dc8190b331c8d205f40284 completed April 6, 2026, 12:39 a.m.
NEDg Description generation batch_69d30254aabc8190966a4398c59a851e completed April 6, 2026, 12:46 a.m.
NED2 Entity disambiguation (via description) batch_69d30305924c8190998cbefa372dca9a completed April 6, 2026, 12:49 a.m.
Created at: March 30, 2026, 9:09 p.m.