Triple
T19101052
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trade Policy Review Body |
E467529
|
entity |
| Predicate | frequencyDeterminedBy |
P13344
|
FINISHED |
| Object | member’s share in world 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: member’s share in world trade | Statement: [Trade Policy Review Body, frequencyDeterminedBy, member’s share in world trade]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: frequencyDeterminedBy Context triple: [Trade Policy Review Body, frequencyDeterminedBy, member’s share in world trade]
-
A.
frequencyDependsOn
chosen
Indicates that the frequency of one event, action, or state is determined or influenced by another factor or condition.
-
B.
frequency
Indicates how often an event, action, or relationship occurs within a given period or context.
-
C.
frequencyCategory
Indicates how often an action, event, or relationship occurs, typically by assigning it to a qualitative frequency level (e.g., rare, occasional, frequent).
-
D.
frequencyChange
Indicates a change in how often an event, action, or state occurs over time.
-
E.
frequencyComparedTo
Indicates how often one event or action occurs relative to another, expressing a comparison of their frequencies.
- 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_69d8dd05ac4c8190b1967d8f97f3fb2f |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e36de7bc8190b353ed59e12e4631 |
completed | April 20, 2026, 8:27 a.m. |
| PD | Predicate disambiguation | batch_69e4b9ac41848190afd0f33b42cebe99 |
completed | April 19, 2026, 11:17 a.m. |
Created at: April 10, 2026, 12:04 p.m.