Triple
T23835722
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Diaporthe |
E590846
|
entity |
| Predicate | infectionCourt |
P153792
|
FINISHED |
| Object | wounds on plants |
—
|
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: wounds on plants | Statement: [Diaporthe, infectionCourt, wounds on plants]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: infectionCourt Context triple: [Diaporthe, infectionCourt, wounds on plants]
-
A.
affectedCourt
Indicates that a particular court is impacted or influenced by a specified action, decision, or legal matter.
-
B.
courts
Indicates that one entity actively seeks the favor, support, or romantic interest of another through deliberate actions or overtures.
-
C.
courtContext
Indicates the legal or judicial setting, circumstances, or framework within which a court-related action or relationship takes place.
-
D.
heldCourtIn
Indicates that an authority or governing body formally conducted judicial or official proceedings in a particular place.
-
E.
courtFeatured
Indicates that a particular court prominently presented, highlighted, or showcased a given entity (such as a case, event, or person) in an official or notable context.
- 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_69e25d1de32c8190a907afe9c3d6cd6d |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1c7f9eaa081909531f1322e0ec9ca |
completed | April 29, 2026, 8:57 a.m. |
| PD | Predicate disambiguation | batch_69f156036ad48190bc2ffdaf39218bcb |
completed | April 29, 2026, 12:51 a.m. |
| PDg | Predicate description generation | batch_69f158b0e320819090b947ee7eb14116 |
completed | April 29, 2026, 1:02 a.m. |
Created at: April 17, 2026, 8:07 p.m.