Triple

T18204266
Position Surface form Disambiguated ID Type / Status
Subject RoBERTa E435864 entity
Predicate paperAuthorsInclude P63068 FINISHED
Object Danqi Chen NE NERFINISHED

How this triple was built (2 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: Danqi Chen | Statement: [RoBERTa, paperAuthorsInclude, Danqi Chen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Danqi Chen
Context triple: [RoBERTa, paperAuthorsInclude, Danqi Chen]
  • A. Danqi Chen chosen
    Danqi Chen is a prominent computer scientist and natural language processing researcher known for her work on neural reading comprehension and information retrieval.
  • B. Tianqi Chen
    Tianqi Chen is a computer scientist and machine learning researcher best known for creating the widely used gradient boosting library XGBoost.
  • C. Xue Chen
    Xue Chen is a prominent Chinese beach volleyball player who has represented China in multiple international competitions, including the Olympic Games.
  • D. Fala Chen
    Fala Chen is a Chinese-American actress known for her work in both Asian television dramas and Hollywood films, including roles in major franchises.
  • E. Xiangmei Chen
    Xiangmei Chen, better known as Anna Chennault, was a prominent Chinese-American journalist, Republican political operative, and influential figure in U.S.–China relations during the Cold War.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b90dba6481908e119eb9aa4ca0cb completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4e222831081908f7d5500424e3acb completed April 19, 2026, 2:09 p.m.
Created at: April 10, 2026, 10:32 a.m.