Triple
T11548946
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rumex |
E273841
|
entity |
| Predicate | includesSpeciesWithUse |
P40129
|
FINISHED |
| Object | edible leafy herbs |
—
|
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: edible leafy herbs | Statement: [Rumex, includesSpeciesWithUse, edible leafy herbs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includesSpeciesWithUse Context triple: [Rumex, includesSpeciesWithUse, edible leafy herbs]
-
A.
containsSpeciesUsedAs
chosen
Indicates that something includes, as part of its composition or content, a particular species that is used for a specified purpose.
-
B.
includesSpecies
Indicates that one entity contains or encompasses one or more species as part of its composition or scope.
-
C.
includesSpeciesFrom
Indicates that one collection, group, or set contains one or more species that originate from or belong to another specified source or context.
-
D.
usedBySpecies
Indicates that something (such as an object, resource, or method) is utilized or employed by a particular species.
-
E.
includesSpeciesCausing
Indicates that one entity contains or encompasses species that are responsible for causing a particular effect, condition, or outcome in another entity.
- 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_69d6aae4dfa48190a3ab0b19a159a3c5 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d886e615b08190a072924329a94a6a |
completed | April 10, 2026, 5:13 a.m. |
| PD | Predicate disambiguation | batch_69d8087e57b48190a4c253dc0210f9d4 |
completed | April 9, 2026, 8:13 p.m. |
Created at: April 8, 2026, 9:37 p.m.