Triple
T1818350
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IR64 |
E40486
|
entity |
| Predicate | hasAmyloseContent |
P32633
|
FINISHED |
| Object | intermediate amylose content |
—
|
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: intermediate amylose content | Statement: [IR64, hasAmyloseContent, intermediate amylose content]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAmyloseContent Context triple: [IR64, hasAmyloseContent, intermediate amylose content]
-
A.
hasSugarContent
Indicates that one entity possesses or contains a specified amount or level of sugar.
-
B.
isCellulosicFiber
Indicates that a material or fiber is composed primarily of cellulose or derived from cellulose-based sources.
-
C.
hasPhloem
Indicates that one entity possesses or contains phloem tissue used for transporting nutrients in plants.
-
D.
hasXylem
Indicates that an entity possesses xylem tissue or structures for conducting water and nutrients.
-
E.
hasMainIngredient
Indicates that one entity is the primary or most significant ingredient used to make another entity.
- 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_69a8864526c081908a3a4d74f689e2c5 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aba67721788190951beae25e885457 |
completed | March 7, 2026, 4:15 a.m. |
| PD | Predicate disambiguation | batch_69aa61d884548190a19cf3a6b5ae9d48 |
completed | March 6, 2026, 5:10 a.m. |
| PDg | Predicate description generation | batch_69aba67554788190b429f2b9f0a70310 |
completed | March 7, 2026, 4:15 a.m. |
Created at: March 4, 2026, 7:32 p.m.