Triple
T16851621
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ichi-Go |
E409687
|
entity |
| Predicate | notableCityCaptured |
P8411
|
FINISHED |
| Object | Guilin |
E235421
|
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: Guilin | Statement: [Ichi-Go, notableCityCaptured, Guilin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Guilin Context triple: [Ichi-Go, notableCityCaptured, Guilin]
-
A.
Guilin
chosen
Guilin is a scenic city in southern China’s Guangxi region, famed for its dramatic karst mountains and picturesque Li River landscapes.
-
B.
Zhangjiajie
Zhangjiajie is a scenic city in northwestern Hunan Province, China, famed for its towering sandstone pillars and dramatic national forest park that inspired the floating mountains in the film "Avatar."
-
C.
Wuzhou
Wuzhou is a prefecture-level city in eastern Guangxi, China, known as a regional transport hub and commercial center along the Xi River.
-
D.
Luyang
Luyang is a historic name associated with the city of Hefei, the capital of Anhui Province in eastern China.
-
E.
Langting
Langting is a small town in the Dima Hasao (formerly North Cachar Hills) district of Assam, India, known as a local administrative and transport hub in the hilly region.
- 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_69d88395e6c88190b22730f335107c14 |
completed | April 10, 2026, 4:59 a.m. |
| NER | Named-entity recognition | batch_69e3b379b8fc81908d8bc9950c7f8bad |
completed | April 18, 2026, 4:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00bb216fac81909d401c6b9911d1e0 |
completed | May 10, 2026, 5:06 p.m. |
Created at: April 10, 2026, 5:24 a.m.