Triple
T24611205
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barbera |
E609117
|
entity |
| Predicate | qualityImpactOfYield |
P156744
|
FINISHED |
| Object | lower yields improve concentration |
—
|
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: lower yields improve concentration | Statement: [Barbera, qualityImpactOfYield, lower yields improve concentration]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: qualityImpactOfYield Context triple: [Barbera, qualityImpactOfYield, lower yields improve concentration]
-
A.
yieldPotential
Indicates the expected amount or capacity of output, production, or benefit that something can generate under given conditions.
-
B.
yieldPotentialComparedToTraditionalVarieties
Indicates how the expected crop yield associated with something compares in magnitude to the yield of conventional or traditional varieties.
-
C.
yieldClassification
Indicates how an outcome, result, or production level is categorized or labeled according to predefined yield criteria.
-
D.
hasGrainQuality
Indicates that an entity possesses a particular level or type of grain quality, characterizing the quality attributes of its grain.
-
E.
agriculturalProductivity
Indicates the level or efficiency of agricultural output produced relative to the resources or inputs used.
- F. None of above. chosen
Provenance (4 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_69e2c4d1140081909c58667bf68f80c3 |
completed | April 17, 2026, 11:40 p.m. |
| NER | Named-entity recognition | batch_69f2be044d4c819094e14eda28d371a7 |
completed | April 30, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69f2a6ca751c8190a040c10d701ecf3a |
completed | April 30, 2026, 12:48 a.m. |
| PDg | Predicate description generation | batch_69f2b8b8bc5881908df49c0b07110246 |
completed | April 30, 2026, 2:04 a.m. |
Created at: April 18, 2026, 2:31 a.m.