Triple
T12952289
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Matanuska Valley |
E309919
|
entity |
| Predicate | daylightEffect |
P107672
|
FINISHED |
| Object | enhanced plant growth in summer |
—
|
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: enhanced plant growth in summer | Statement: [Matanuska Valley, daylightEffect, enhanced plant growth in summer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: daylightEffect Context triple: [Matanuska Valley, daylightEffect, enhanced plant growth in summer]
-
A.
lightPeriod
Indicates the duration or interval during which light is present or active in a given context.
-
B.
illuminationCondition
Indicates the lighting or brightness conditions under which an event, observation, or interaction takes place.
-
C.
isDiurnal
Indicates that an entity is active during the daytime and rests at night.
-
D.
dayLengthCharacteristic
Indicates a relationship where an entity is characterized or defined by the length or duration of its day.
-
E.
lightLevel
Indicates the intensity or amount of light present in a given context or environment.
- 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_69d7bdfb57a88190836b743e2825feca |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d97e59a4c88190907d05b8d57dae89 |
completed | April 10, 2026, 10:48 p.m. |
| PD | Predicate disambiguation | batch_69d97dba57988190b786ffed55687a72 |
completed | April 10, 2026, 10:46 p.m. |
| PDg | Predicate description generation | batch_69d97e5811f481908178fac6d2e0efcd |
completed | April 10, 2026, 10:48 p.m. |
Created at: April 9, 2026, 5:43 p.m.