Triple
T31508823
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Muse |
E803888
|
entity |
| Predicate | mainTradePartnerCountry |
P26129
|
FINISHED |
| Object | China |
—
|
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: China | Statement: [Muse, mainTradePartnerCountry, China]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainTradePartnerCountry Context triple: [Muse, mainTradePartnerCountry, China]
-
A.
mainTradingPartnerCountry
chosen
Indicates the country that serves as the primary trading partner for a given entity, based on the largest or most significant volume of trade.
-
B.
tradePartnerRegion
Indicates that one entity engages in trade with partners located in a specified geographic region.
-
C.
countryPartner
Indicates a formal partnership relationship between two countries, such as cooperation, alliance, or strategic collaboration.
-
D.
mainTradingPartnerRegion
Indicates the geographic region that serves as the primary trading partner for a given entity.
-
E.
countryTradeShare
Indicates the proportion of a country’s total trade that is conducted with a specific partner or in a specific category.
- F. None of above.
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_69f348ceb0a48190ae7feca263b6296c |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f7764ab1fc81909f9348db87bd7692 |
completed | May 3, 2026, 4:22 p.m. |
| PD | Predicate disambiguation | batch_69f76905d9c88190b1ee810bc9ab644f |
completed | May 3, 2026, 3:25 p.m. |
Created at: April 30, 2026, 9:48 p.m.