Triple
T1804945
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oryza glaberrima |
E40199
|
entity |
| Predicate | toleranceToLocalStresses |
P32572
|
FINISHED |
| Object | high |
—
|
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: high | Statement: [Oryza glaberrima, toleranceToLocalStresses, high]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: toleranceToLocalStresses Context triple: [Oryza glaberrima, toleranceToLocalStresses, high]
-
A.
tolerates
Indicates that one entity endures, accepts, or allows the presence, behavior, or condition of another entity without intervening to stop or change it.
-
B.
allowsSpatialCurvature
Indicates that one entity permits or enables the presence or variation of spatial curvature in relation to another entity or context.
-
C.
transportTolerance
Indicates the degree to which an entity can withstand or remain functional under the conditions and stresses of being transported.
-
D.
tension
Indicates a state of strain, stress, or conflict existing between entities, often involving opposing forces, interests, or emotions.
-
E.
localSymmetry
Indicates that an entity exhibits symmetry within a localized region or subset of its structure, rather than across its entire extent.
- 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_69a88643a3388190a612f2ebe1fb29e7 |
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_69aa61d514c081908197ac1f7c7d7a88 |
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.