Triple
T24609306
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anthonomus grandis |
E609070
|
entity |
| Predicate | targetPlantPart |
P41548
|
FINISHED |
| Object | cotton squares |
—
|
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: cotton squares | Statement: [Anthonomus grandis, targetPlantPart, cotton squares]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetPlantPart Context triple: [Anthonomus grandis, targetPlantPart, cotton squares]
-
A.
hasPlantPart
Indicates that one entity includes, contains, or is composed of a specific plant part of another entity.
-
B.
affectsPlantPart
chosen
Indicates that one entity produces an influence, change, or impact on a specific part of a plant.
-
C.
hostsPlantOf
Indicates that one entity serves as a host environment or substrate on which a particular plant lives, grows, or depends.
-
D.
ediblePart
Indicates that one entity is a part of another entity that can be eaten or consumed.
-
E.
usedInPlant
Indicates that something is utilized or applied within a plant, such as in its processes, operations, or systems.
- 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_69e2c4d060e08190ac9f7c49b1036e20 |
completed | April 17, 2026, 11:40 p.m. |
| NER | Named-entity recognition | batch_69f2be044d4c819094e14eda28d371a7 |
completed | April 30, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69f2a6ca751c8190a040c10d701ecf3a |
completed | April 30, 2026, 12:48 a.m. |
Created at: April 18, 2026, 2:31 a.m.