Triple
T989622
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cupressus sempervirens |
E21357
|
entity |
| Predicate | evergreenFoliage |
P5989
|
FINISHED |
| Object | dark green |
—
|
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: dark green | Statement: [Cupressus sempervirens, evergreenFoliage, dark green]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: evergreenFoliage Context triple: [Cupressus sempervirens, evergreenFoliage, dark green]
-
A.
evergreenHabit
chosen
Indicates that a plant maintains its foliage year-round rather than shedding leaves seasonally.
-
B.
evergreen
Indicates that something remains persistently relevant, active, or unchanged over time, without becoming outdated or obsolete.
-
C.
typicalLeafCharacteristic
Indicates the usual or defining features of a leaf that characterize it under normal conditions.
-
D.
vegetation
Indicates that an area or object is covered with, contains, or is characterized by plant life.
-
E.
vegetationType
Indicates the specific kind or category of plant cover or flora that characterizes a given area or environment.
- 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_69a493c383dc8190a03257f22d4b4183 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b4aa16f081909dcc7a7ce3fb1b64 |
completed | March 1, 2026, 9:50 p.m. |
| PD | Predicate disambiguation | batch_69a4b2adbde48190b07966d0c3179516 |
completed | March 1, 2026, 9:42 p.m. |
Created at: March 1, 2026, 7:41 p.m.