Triple
T8949632
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chen Zhu |
E213311
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Chen |
E113104
|
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: [Chen Zhu, familyName, Chen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chen Context triple: [Chen Zhu, familyName, Chen]
-
A.
Chen
chosen
Chen is a common Chinese surname borne by many notable individuals across politics, arts, science, and technology.
-
B.
Ching
Ching is the surname of Brian Ching, a retired American soccer player best known as a forward for the Houston Dynamo and the U.S. national team.
-
C.
Cheng
Cheng is a given name associated with the Chinese politician Chen Cheng.
-
D.
Shen
Shen is a Chinese surname historically borne by notable figures such as the Song dynasty polymath Shen Kuo.
-
E.
Chih-chung
Chih-chung is an alternative romanization of the Chinese given name Zhizhong, used in older or non–pinyin transcription systems.
- 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_69ca839843408190a39069a029a89f15 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc670b5f50819080f1c73992fe5281 |
completed | April 1, 2026, 12:30 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfc206550c8190abf016f25b14fa64 |
completed | April 3, 2026, 1:35 p.m. |
Created at: March 30, 2026, 6:59 p.m.