Triple
T1759231
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fungi |
E38617
|
entity |
| Predicate | nutritionMechanism |
P29817
|
FINISHED |
| Object | Absorptive nutrition |
—
|
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: Absorptive nutrition | Statement: [Fungi, nutritionMechanism, Absorptive nutrition]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nutritionMechanism Context triple: [Fungi, nutritionMechanism, Absorptive nutrition]
-
A.
nutritionType
Indicates the specific category or kind of nutritional characteristic or value associated with an entity.
-
B.
diet
Indicates that an entity regularly consumes a particular type or range of food as its primary source of nutrition.
-
C.
feedingStructure
Indicates a relationship where one entity serves as the anatomical or mechanical structure used by another entity to obtain or ingest food.
-
D.
metabolismType
chosen
Indicates the kind of metabolic process or pathway an entity uses to obtain and transform energy or nutrients.
-
E.
foodEffect
Indicates how consuming a particular food influences or changes another entity, such as an organism, condition, or process.
- 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_69a8862d562481908d7025a1c1f67c0d |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69ab173936b4819097332ee185996bbd |
completed | March 6, 2026, 6:04 p.m. |
| PD | Predicate disambiguation | batch_69aa61c9e06c819085489e00cfe72153 |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:31 p.m.