Triple
T2647222
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ophiostoma quercus |
E53811
|
entity |
| Predicate | symptomOnHost |
P2896
|
FINISHED |
| Object | brown to dark streaks in sapwood |
—
|
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: brown to dark streaks in sapwood | Statement: [Ophiostoma quercus, symptomOnHost, brown to dark streaks in sapwood]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: symptomOnHost Context triple: [Ophiostoma quercus, symptomOnHost, brown to dark streaks in sapwood]
-
A.
symptom
chosen
Indicates that a particular condition, disease, or problem manifests through a specific observable sign or complaint.
-
B.
lesionAssociatedWithSymptom
Indicates that a particular lesion is linked to, or occurs together with, a specific symptom.
-
C.
infectsTissue
Indicates that one entity (typically a pathogen or agent) invades and establishes itself within the tissue of another entity.
-
D.
parasitizes
Indicates a relationship in which one organism lives on or in another organism, deriving nutrients or benefits at the host’s expense.
-
E.
featuresDisease
Indicates that an entity exhibits, presents, or is characterized by a particular disease.
- 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_69ab495e192081909c77b622e8e7e15a |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abd919bf2c81908feb768f3391e985 |
completed | March 7, 2026, 7:51 a.m. |
| PD | Predicate disambiguation | batch_69abd814298c8190952f05aed43f6bb8 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:53 p.m.