Triple
T12515640
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | EdDSA |
E299184
|
entity |
| Predicate | introducedBy |
P513
|
FINISHED |
| Object | Bo-Yin Yang |
E832820
|
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: Bo-Yin Yang | Statement: [EdDSA, introducedBy, Bo-Yin Yang]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bo-Yin Yang Context triple: [EdDSA, introducedBy, Bo-Yin Yang]
-
A.
Bo-Yin Yang
chosen
Bo-Yin Yang is a Taiwanese cryptographer known for his contributions to modern public-key cryptography, including work related to the Ed25519 signature scheme.
-
B.
Chiwei Yu
Chiwei Yu is a small, remote islet in the East China Sea that is part of the disputed Diaoyutai/Senkaku Islands archipelago.
-
C.
Fenggang Yang
Fenggang Yang is a prominent Chinese-American sociologist known for his influential research on religion and religious change in contemporary China.
-
D.
Ching-Yun Hu
Ching-Yun Hu is a Taiwanese-American concert pianist acclaimed for her international competition successes and performances with major orchestras worldwide.
-
E.
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.
- 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_69d6ada5cdd48190860d9ce30aff69be |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d9541f80148190976d1d912fe155d0 |
completed | April 10, 2026, 7:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f655745cec8190b5582eb4a339d501 |
completed | May 2, 2026, 7:50 p.m. |
Created at: April 8, 2026, 9:57 p.m.