Triple
T22540809
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kingdom of Wei (Three Kingdoms, regional capital) |
E557282
|
entity |
| Predicate | usedEraName |
P91459
|
FINISHED |
| Object | Ganlu |
—
|
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: Ganlu | Statement: [Kingdom of Wei (Three Kingdoms, regional capital), usedEraName, Ganlu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ganlu Context triple: [Kingdom of Wei (Three Kingdoms, regional capital), usedEraName, Ganlu]
-
A.
Ganlu
chosen
Ganlu was a historical Chinese era name used during the Cao Wei state of the Three Kingdoms period.
-
B.
Liguo
Liguo is a Chinese given name commonly used for males and borne by various individuals across different fields.
-
C.
Guanggu
Guanggu is a major high-tech development zone in Wuhan, China, known as an innovation hub for the optics and electronics industries.
-
D.
Guan
Guan is a common Chinese surname with historical roots and multiple romanized variants, including Kwan.
-
E.
Xianchu
Xianchu is the given name of Han Xianchu, a prominent Chinese military commander known for his role in the Chinese Civil War and the Korean War.
- 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_69e11e58662081909ae346ab384514ca |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15f3251808190a72b849157854d8d |
completed | April 29, 2026, 1:30 a.m. |
Created at: April 16, 2026, 8:51 p.m.