Triple
T7746842
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cristina Yang |
E175652
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Yang |
E84692
|
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: Yang | Statement: [Cristina Yang, familyName, Yang]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yang Context triple: [Cristina Yang, familyName, Yang]
-
A.
Yang
chosen
Yang is a common Chinese surname with deep historical roots and widespread use across Chinese-speaking communities.
-
B.
Ying
Ying was the principal political and cultural center of the ancient Chinese State of Chu during the Zhou dynasty period.
-
C.
Yong
Yong is a variant transliteration of the Chinese surname and given name commonly romanized as Yang.
-
D.
Yin
Yin was the last and most prominent capital city of China’s Shang dynasty, serving as its political and cultural center.
-
E.
Yih
Yih is the surname of Chia-Shun Yih, a notable Chinese-American engineer and fluid dynamicist.
- 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_69c69960b3588190a53aa590d31d9544 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c7038caa64819084f61b42a73c2d8b |
completed | March 27, 2026, 10:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8be50ac4881909b537f513bed2edd |
completed | March 29, 2026, 5:53 a.m. |
Created at: March 27, 2026, 4:08 p.m.