Triple
T13659091
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baruten |
E326937
|
entity |
| Predicate | hasBorderTrade |
P94594
|
FINISHED |
| Object | Yes |
—
|
LITERAL 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: Yes | Statement: [Baruten, hasBorderTrade, Yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBorderTrade Context triple: [Baruten, hasBorderTrade, Yes]
-
A.
hasCrossBorderTrade
chosen
Indicates that there is trade or commercial exchange occurring between entities located in different countries or jurisdictions.
-
B.
borderTradeType
Indicates the specific category or nature of trade that occurs across a border between two regions or countries.
-
C.
borderTradePointWith
Indicates a location or facility where trade or commercial exchange occurs between two bordering regions or countries.
-
D.
hasBorderPostWith
Indicates that two regions or territories share a border where an official border post or checkpoint is located between them.
-
E.
hasBorderMeetingCountry
Indicates that one country shares a land or maritime border with another country.
- 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_69d8076d8270819092afc2f0e9c359a8 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc61f0d808190b1cd2a6ba0d930eb |
completed | April 12, 2026, 4:19 p.m. |
| PD | Predicate disambiguation | batch_69dbbe8a027081908d8f884b89707a5e |
completed | April 12, 2026, 3:47 p.m. |
Created at: April 9, 2026, 9:52 p.m.