Triple
T23340748
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charlie Soong |
E591727
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object | Wenchang |
—
|
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: Wenchang | Statement: [Charlie Soong, placeOfBirth, Wenchang]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wenchang Context triple: [Charlie Soong, placeOfBirth, Wenchang]
-
A.
Wenchang
chosen
Wenchang is a coastal city in northeastern Hainan, China, known as a cultural center and important homeland of many overseas Chinese.
-
B.
Wanning
Wanning is a county-level coastal city in southeastern Hainan, China, known for its tropical climate, beaches, and surf-friendly bays.
-
C.
Xingsha
Xingsha is a town in Changsha County, Hunan Province, China, known as the modern urban area closest to the famous Mawangdui Han Tombs archaeological site.
-
D.
Lingshui
Lingshui is a coastal county-level city in southeastern Hainan, China, known for its tropical climate, beaches, and growing tourism industry.
-
E.
Haikou
Haikou is the capital and largest city of China’s Hainan Province, known as a key port, commercial hub, and tropical coastal destination.
- 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_69e25d20e3d08190bcede87673cafb25 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f198329d9c8190992627afa9b54bed |
completed | April 29, 2026, 5:33 a.m. |
Created at: April 17, 2026, 5:18 p.m.