Triple
T139468
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pinophyta |
E2819
|
entity |
| Predicate | evergreenHabit |
P5989
|
FINISHED |
| Object | mostly evergreen |
—
|
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: mostly evergreen | Statement: [Pinophyta, evergreenHabit, mostly evergreen]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: evergreenHabit Context triple: [Pinophyta, evergreenHabit, mostly evergreen]
-
A.
vegetation
Indicates that an area or object is covered with, contains, or is characterized by plant life.
-
B.
vegetationType
Indicates the specific kind or category of plant cover or flora that characterizes a given area or environment.
-
C.
hardiness
Indicates the degree to which an entity can withstand or endure harsh, adverse, or challenging conditions.
-
D.
plantType
Indicates the specific kind or category of plant that an entity is classified as.
-
E.
droughtTolerance
Indicates the degree to which an entity can maintain normal function and survival under conditions of limited water availability.
- 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_69a2521e35c08190b28e5c9f1e3c9b59 |
completed | Feb. 28, 2026, 2:25 a.m. |
| NER | Named-entity recognition | batch_69a257c679d88190bc71775dab2cfc64 |
completed | Feb. 28, 2026, 2:49 a.m. |
| PD | Predicate disambiguation | batch_69a2565426c08190aab68e34a6a2d60e |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a25737f9188190b9690dce98aed83a |
completed | Feb. 28, 2026, 2:47 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.