Triple

T15313838
Position Surface form Disambiguated ID Type / Status
Subject Caffe E366103 entity
Predicate developer P73 FINISHED
Object Yangqing Jia E480174 NE FINISHED

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: Yangqing Jia | Statement: [Caffe, developer, Yangqing Jia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yangqing Jia
Context triple: [Caffe, developer, Yangqing Jia]
  • A. Yangqing Jia chosen
    Yangqing Jia is a computer scientist and software engineer known for his influential work in deep learning and computer vision, including contributions to convolutional neural network architectures and open-source frameworks.
  • B. Yang Sun
    Yang Sun is an opportunistic, morally ambiguous pilot whose relationship with the protagonist Shen Te highlights themes of selfishness and survival in Bertolt Brecht’s play "The Good Person of Szechwan."
  • C. Younan Xia
    Younan Xia is a prominent chemist and materials scientist known for his pioneering work in nanomaterials synthesis and nanotechnology.
  • D. Yu Qingfang
    Yu Qingfang was a key revolutionary leader associated with the Tapani Incident, an anti-Japanese uprising in early 20th-century Taiwan.
  • E. Yu Xuezhong
    Yu Xuezhong was a prominent Chinese military leader associated with the Northeastern Army during the Republican era.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d85a113ee881908e297a1d38dd79fa completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03dd050108190a584543cb93943a4 completed April 16, 2026, 1:39 a.m.
NED1 Entity disambiguation (via context triple) batch_69fef8a3da3881909b50cfbec0543adc completed May 9, 2026, 9:04 a.m.
Created at: April 10, 2026, 3:16 a.m.