Triple
T15361414
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ResNeXt |
E367297
|
entity |
| Predicate | paperAuthors |
P2002
|
FINISHED |
| Object |
Saining Xie
Saining Xie is a computer vision researcher known for his influential work on deep convolutional neural network architectures, including the ResNeXt model.
|
E1159757
|
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: Saining Xie | Statement: [ResNeXt, paperAuthors, Saining Xie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Saining Xie Context triple: [ResNeXt, paperAuthors, Saining Xie]
-
A.
Xing Li
Xing Li is a computer networking expert known for co-authoring IETF standards, including RFC 6145 on IPv4/IPv6 translation mechanisms.
-
B.
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.
-
C.
Yiping Gan
Yiping Gan is a regional variety of Gan Chinese, a Sinitic language spoken primarily in Jiangxi province and surrounding areas.
-
D.
Xiaodong Chen
Xiaodong Chen is a prominent materials scientist and nanotechnology researcher who serves as editor-in-chief of the journal ACS Nano.
-
E.
Xindong Wu
Xindong Wu is a prominent computer scientist known for his influential contributions to data mining and knowledge discovery research.
- 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: Saining Xie Triple: [ResNeXt, paperAuthors, Saining Xie]
Generated description
Saining Xie is a computer vision researcher known for his influential work on deep convolutional neural network architectures, including the ResNeXt model.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Saining Xie Target entity description: Saining Xie is a computer vision researcher known for his influential work on deep convolutional neural network architectures, including the ResNeXt model.
-
A.
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.
-
B.
Xing Li
Xing Li is a computer networking expert known for co-authoring IETF standards, including RFC 6145 on IPv4/IPv6 translation mechanisms.
-
C.
Yiping Gan
Yiping Gan is a regional variety of Gan Chinese, a Sinitic language spoken primarily in Jiangxi province and surrounding areas.
-
D.
Xiaodong Chen
Xiaodong Chen is a prominent materials scientist and nanotechnology researcher who serves as editor-in-chief of the journal ACS Nano.
-
E.
Xindong Wu
Xindong Wu is a prominent computer scientist known for his influential contributions to data mining and knowledge discovery research.
- 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_69d85a1483788190ad93c2748e8af34b |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e4607408190ab281a7f7a8012d3 |
completed | April 16, 2026, 1:41 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff2cec4f2481908fae5209bfd48dcf |
completed | May 9, 2026, 12:47 p.m. |
| NEDg | Description generation | batch_69ff2e7bf8c881909fecb6cf86bc32f2 |
completed | May 9, 2026, 12:54 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff331c267c8190bbc26ddd47273be7 |
completed | May 9, 2026, 1:14 p.m. |
Created at: April 10, 2026, 3:18 a.m.