Triple
T501251
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Magnoliophyta |
E10404
|
entity |
| Predicate | diversity |
P14432
|
FINISHED |
| Object | most diverse group of land plants |
—
|
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: most diverse group of land plants | Statement: [Magnoliophyta, diversity, most diverse group of land plants]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: diversity Context triple: [Magnoliophyta, diversity, most diverse group of land plants]
-
A.
centerOfDiversity
Indicates the location where a particular group, trait, or phenomenon exhibits its greatest variety or concentration of diversity.
-
B.
culturalVariation
Indicates that there are differences in practices, beliefs, or expressions between cultures or within a culture across groups, contexts, or time.
-
C.
distinction
Indicates that one entity is recognized, treated, or classified as different or separate from another.
-
D.
genreDiversity
Indicates the extent to which an entity involves, includes, or spans multiple distinct genres rather than being confined to a single genre.
-
E.
demographics
Indicates the relationship of providing or characterizing statistical information about a population’s attributes, such as age, gender, income, or education.
- 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_69a2e848adf881908e5e04f7af030093 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f131e2148190afd43402f505c73e |
completed | Feb. 28, 2026, 1:44 p.m. |
| PD | Predicate disambiguation | batch_69a2edfbb7e0819092cf29c2c68fe8fb |
completed | Feb. 28, 2026, 1:30 p.m. |
| PDg | Predicate description generation | batch_69a2eebbd70481908b462296671de67b |
completed | Feb. 28, 2026, 1:33 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.