Triple
T21950174
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Qi |
E542044
|
entity |
| Predicate | capital |
P234
|
FINISHED |
| Object | Linzi |
—
|
NE NERFINISHED |
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: Linzi | Statement: [Qi, capital, Linzi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Linzi Context triple: [Qi, capital, Linzi]
-
A.
Linzi
chosen
Linzi was the prominent ancient Chinese city that served as the political, economic, and cultural center of the powerful State of Qi during the Zhou dynasty.
-
B.
Jiali
Jiali is the original Chinese title of the work known in English as "Family Rituals."
-
C.
Ziying
Ziying was the last ruler of the Qin dynasty in ancient China, whose brief reign ended with the dynasty’s collapse and the rise of the Han.
-
D.
Ziyi
Ziyi is the given name of Zhang Ziyi, a renowned Chinese actress known internationally for her roles in films such as "Crouching Tiger, Hidden Dragon" and "Memoirs of a Geisha."
-
E.
Yinzhi
Yinzhi was a Qing dynasty imperial prince, known as one of the sons of the Kangxi Emperor of China.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c47ef0e48190a50e1bcc43f4b3fd |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f1243bb9c88190a3774b9fa2af9871 |
completed | April 28, 2026, 9:18 p.m. |
Created at: April 16, 2026, 7:58 p.m.