Triple
T735518
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chan |
E14920
|
entity |
| Predicate | hasVariantSpelling |
P457
|
FINISHED |
| Object | Chen |
E14920
|
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: Chen | Statement: [Chan, hasVariantSpelling, Chen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chen Context triple: [Chan, hasVariantSpelling, Chen]
-
A.
Zeng
Zeng is a Chinese surname and given name commonly rendered in pinyin and borne by numerous historical and contemporary figures in China.
-
B.
Wu
Wu is a common Chinese surname borne by many notable individuals across politics, academia, entertainment, and sports.
-
C.
Chan
chosen
Chan is a common Chinese surname shared by many notable individuals across various fields worldwide.
-
D.
Chun
Chun is the given name of Peng Chun Chang, a prominent Chinese philosopher and diplomat who helped draft the Universal Declaration of Human Rights.
-
E.
Xuan
Xuan is a Vietnamese surname commonly used as a family name in Vietnam.
- 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_69a4934d9930819099eed80096b0597d |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a5da30b88190afbd12ae6109cc1b |
completed | March 1, 2026, 8:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a673329a0c8190b725b9863ba4c162 |
completed | March 3, 2026, 5:35 a.m. |
Created at: March 1, 2026, 7:37 p.m.