Triple
T3340094
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Spanish real |
E70236
|
entity |
| Predicate | usedInTrade |
P511
|
FINISHED |
| Object | Atlantic trade |
—
|
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: Atlantic trade | Statement: [Spanish real, usedInTrade, Atlantic trade]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedInTrade Context triple: [Spanish real, usedInTrade, Atlantic trade]
-
A.
usedInInternationalTrade
chosen
Indicates that something participates as a good, service, or instrument in commercial exchanges between different countries.
-
B.
usedInECommerce
Indicates that something is employed or applied within the context of electronic commerce activities or systems.
-
C.
tradedIn
Indicates that one entity has given up or exchanged another entity, typically as part of a transaction to obtain something else.
-
D.
areUsedIn
Indicates that certain entities serve as components, tools, or resources within a particular process, context, or application.
-
E.
usedAgainst
Indicates that one entity is employed, applied, or deployed in opposition to, or for the purpose of affecting, another entity.
- 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_69ad85a405e48190b6e68de7cf9f319e |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb1bf1f648190993ac8e9dda60983 |
completed | March 8, 2026, 5:28 p.m. |
| PD | Predicate disambiguation | batch_69ada42c2ba8819091136805ce17b39d |
completed | March 8, 2026, 4:30 p.m. |
Created at: March 8, 2026, 3:12 p.m.