Triple
T17604144
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rhoicissus |
E428780
|
entity |
| Predicate | leafComplexity |
P128249
|
FINISHED |
| Object | simple leaves |
—
|
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: simple leaves | Statement: [Rhoicissus, leafComplexity, simple leaves]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leafComplexity Context triple: [Rhoicissus, leafComplexity, simple leaves]
-
A.
hasComplexity
Indicates that something possesses a certain level or type of complexity, often in terms of structure, behavior, or difficulty.
-
B.
parsingComplexity
Indicates the level of difficulty or computational effort required to parse or analyze a given input or structure.
-
C.
hasComplex
Indicates that one entity possesses, is associated with, or is part of a larger composite structure or complex formed with another entity.
-
D.
leafNumberCharacteristic
Indicates a relationship where an entity is associated with a specific count or quantitative characteristic of its leaves.
-
E.
morphologicalComplexity
Indicates the degree to which a language’s word forms are structurally intricate, involving multiple morphemes, inflections, or derivational processes.
- 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_69d889e1c6148190ba76241e74688f8b |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e46c4b4ee88190827ea28b99ca6f33 |
completed | April 19, 2026, 5:46 a.m. |
| PD | Predicate disambiguation | batch_69e3cdd7da34819099bc9481c5a79bab |
completed | April 18, 2026, 6:30 p.m. |
| PDg | Predicate description generation | batch_69e3cfaac2b881909e1140339eb1a0dd |
completed | April 18, 2026, 6:38 p.m. |
Created at: April 10, 2026, 5:51 a.m.