Triple
T320886
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lupinus texensis |
E6411
|
entity |
| Predicate | sunExposure |
P1346
|
FINISHED |
| Object | full sun |
—
|
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: full sun | Statement: [Lupinus texensis, sunExposure, full sun]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sunExposure Context triple: [Lupinus texensis, sunExposure, full sun]
-
A.
sunRequirement
chosen
Indicates the amount or type of sunlight an entity (such as a plant or object) needs or is designed to receive.
-
B.
SunLocation
Indicates the spatial position or placement of the sun relative to a reference point or environment.
-
C.
hasMaximumSolarInsolation
Indicates that an entity receives the highest level of solar radiation or sunlight intensity compared to relevant alternatives or within a given context.
-
D.
hasMinimumSolarInsolation
Indicates that an entity receives at least a specified minimum amount of solar energy (insolation) over a given area and time period.
-
E.
solarPosition
Indicates the spatial orientation or location of an entity relative to the Sun at a given time.
- 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_69a2e7933d6c8190bb2592ad13286ef2 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2ea8047c08190872c875e00f6e7dd |
completed | Feb. 28, 2026, 1:15 p.m. |
| PD | Predicate disambiguation | batch_69a2e946607081909c8b97473aaf8d1b |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.