Triple
T34132293
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hesbaye |
E875457
|
entity |
| Predicate | highestUse |
P35920
|
FINISHED |
| Object | arable farming |
—
|
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: arable farming | Statement: [Hesbaye, highestUse, arable farming]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: highestUse Context triple: [Hesbaye, highestUse, arable farming]
-
A.
maximumUsage
Indicates the highest allowable or observed amount, frequency, or extent to which something can be used within a defined context or period.
-
B.
usagePeak
Indicates that the usage or consumption of something reaches its highest level or intensity during a particular time or condition.
-
C.
peakUse
chosen
Indicates the time, condition, or context in which something reaches its maximum level of use or intensity.
-
D.
hasHighest
Indicates that one entity possesses the greatest value, rank, or level in a specified attribute or set compared to all others.
-
E.
latestCommonUse
Indicates the most recent point in time at which two or more entities were used or applicable in common.
- 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_69f349aa33848190a2e6c5e4533c8444 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69fd389cb28c819099a77e28d25f258a |
completed | May 8, 2026, 1:13 a.m. |
| PD | Predicate disambiguation | batch_69fd3826d8048190ada79a5868d1d7f3 |
completed | May 8, 2026, 1:11 a.m. |
Created at: May 1, 2026, 1:53 a.m.