Triple
T12812677
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beihai railway station |
E306309
|
entity |
| Predicate | hasOwnerCountry |
P846
|
FINISHED |
| Object | China |
E5561
|
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: China | Statement: [Beihai railway station, hasOwnerCountry, China]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: China Context triple: [Beihai railway station, hasOwnerCountry, China]
-
A.
China
chosen
China is a vast East Asian country known for its long continuous civilization, large population, and major global economic and political influence.
-
B.
Kinas
Kinas is the official rooster mascot created for the UEFA Euro 2004 football championship held in Portugal.
-
C.
Chung Kuo
"Chung Kuo" is an instrumental electronic music track by Vangelis from his 1979 album "China," evoking an atmospheric, synthesizer-driven portrait of China.
-
D.
kina
Kina is the official currency of Papua New Guinea, used for everyday transactions and financial activities throughout the country.
-
E.
Chini
Chini is a town that is twinned with Günzburg, Germany, as part of an international municipal partnership.
- 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_69d7bdf46c448190b1faa55aaacb6317 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96e9adcf08190a12801adcc613477 |
completed | April 10, 2026, 9:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6af49d2c4819097168712af7d4c15 |
completed | May 3, 2026, 2:13 a.m. |
Created at: April 9, 2026, 5:31 p.m.