Triple
T18205035
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LayoutLM |
E435880
|
entity |
| Predicate | hasAuthor |
P4244
|
FINISHED |
| Object |
Lei Cui
Lei Cui is a computer scientist and AI researcher known for his work on document understanding and the development of models such as LayoutLM.
|
E1329379
|
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: Lei Cui | Statement: [LayoutLM, hasAuthor, Lei Cui]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lei Cui Context triple: [LayoutLM, hasAuthor, Lei Cui]
-
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.
Liwen Shao
Liwen Shao is a brilliant and ambitious Chinese businesswoman and technologist in the Pacific Rim universe, known for her pivotal role in developing advanced Jaeger drone technology.
-
D.
Langche Zeng
Langche Zeng is a political scientist and quantitative methodologist known for his collaborative work with Gary King on statistical methods in social science research.
-
E.
Wei Li
Wei Li is a computer scientist known for co-authoring and introducing the T5 (Text-to-Text Transfer Transformer) language model in natural language processing 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: Lei Cui Triple: [LayoutLM, hasAuthor, Lei Cui]
Generated description
Lei Cui is a computer scientist and AI researcher known for his work on document understanding and the development of models such as LayoutLM.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lei Cui Target entity description: Lei Cui is a computer scientist and AI researcher known for his work on document understanding and the development of models such as LayoutLM.
-
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.
Liwen Shao
Liwen Shao is a brilliant and ambitious Chinese businesswoman and technologist in the Pacific Rim universe, known for her pivotal role in developing advanced Jaeger drone technology.
-
D.
Langche Zeng
Langche Zeng is a political scientist and quantitative methodologist known for his collaborative work with Gary King on statistical methods in social science research.
-
E.
Wei Li
Wei Li is a computer scientist known for co-authoring and introducing the T5 (Text-to-Text Transfer Transformer) language model in natural language processing 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_69d8b90dba6481908e119eb9aa4ca0cb |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4e222831081908f7d5500424e3acb |
completed | April 19, 2026, 2:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a049159cbe081908872d559d3fa57a7 |
completed | May 13, 2026, 2:57 p.m. |
| NEDg | Description generation | batch_6a049275f2c08190b9be34f87b05841a |
completed | May 13, 2026, 3:02 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0492fb82348190a3639ca54ac6f014 |
completed | May 13, 2026, 3:04 p.m. |
Created at: April 10, 2026, 10:32 a.m.