Triple
T812626
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Argemone |
E17577
|
entity |
| Predicate | hasCommonNameForSpecies |
P13147
|
FINISHED |
| Object | Mexican poppy |
—
|
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: Mexican poppy | Statement: [Argemone, hasCommonNameForSpecies, Mexican poppy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCommonNameForSpecies Context triple: [Argemone, hasCommonNameForSpecies, Mexican poppy]
-
A.
includesSpecies
Indicates that one entity contains or encompasses one or more species as part of its composition or scope.
-
B.
hasOnlySpecies
Indicates that an entity is associated exclusively with a single specified species and no others.
-
C.
typeSpecies
Indicates that a species is the designated type species that defines and anchors the taxonomic concept of a higher-level group (such as a genus).
-
D.
hasLatinName
Indicates that an entity is associated with a specific Latin (scientific) name.
-
E.
includesCommonName
chosen
Indicates that one entity contains or specifies a commonly used (non-scientific) name for 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_69a4937ae8a08190b5084a03d532b30e |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4ab4c7418819085cb64c6bf5fa70c |
completed | March 1, 2026, 9:10 p.m. |
| PD | Predicate disambiguation | batch_69a4aa73df08819096d0553a4b2509de |
completed | March 1, 2026, 9:07 p.m. |
Created at: March 1, 2026, 7:38 p.m.