Triple
T23285256
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 泰州 |
E588968
|
entity |
| Predicate | 国家 |
P65335
|
FINISHED |
| Object | 中国 |
—
|
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: 中国 | Statement: [泰州, 国家, 中国]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 中国 Context triple: [泰州, 国家, 中国]
-
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.
China
China is a themed area within PortAventura Park that recreates Chinese architecture, culture, and landscapes through rides, shows, and immersive decor.
-
C.
陸中国
陸中国 was an ancient province of Japan located in the central part of present-day Tōhoku, roughly corresponding to modern Iwate Prefecture.
-
D.
Çine
Çine is a district and town in southwestern Turkey known for its agricultural activities and location within Aydın Province in the Aegean region.
-
E.
中国地方
中国地方は、日本本州西部に位置し、広島県や岡山県などを含む歴史と自然に富んだ地域です。
- 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_69e25d16e2c08190a291de254703129e |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1964600888190b40ecbefdc8aec64 |
completed | April 29, 2026, 5:25 a.m. |
Created at: April 17, 2026, 4:59 p.m.