Triple
T6393006
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Diaporthales |
E143872
|
entity |
| Predicate | includesGenus |
P1393
|
FINISHED |
| Object |
Cryphonectria
Cryphonectria is a genus of plant-pathogenic fungi best known for containing the species that causes chestnut blight.
|
E590847
|
NE FINISHED |
How this triple was built (4 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: Cryphonectria | Statement: [Diaporthales, includesGenus, Cryphonectria]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cryphonectria Context triple: [Diaporthales, includesGenus, Cryphonectria]
-
A.
Nectria
Nectria is a genus of fungi in the order Hypocreales, many species of which are known as plant pathogens causing cankers and other diseases on trees and crops.
-
B.
Ophiostoma
Ophiostoma is a genus of fungi best known for containing species that cause Dutch elm disease in elm trees.
-
C.
Ophiostoma piceae
Ophiostoma piceae is a species of sap-staining fungus commonly associated with coniferous trees and known for causing blue stain in lumber.
-
D.
Ceratocystis
Ceratocystis is a genus of plant-pathogenic fungi known for causing wilt and canker diseases in a wide range of trees and crops.
-
E.
Raffaelea
Raffaelea is a genus of fungi known for its symbiotic associations with bark beetles and its role in causing plant diseases such as laurel wilt.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Cryphonectria Triple: [Diaporthales, includesGenus, Cryphonectria]
Generated description
Cryphonectria is a genus of plant-pathogenic fungi best known for containing the species that causes chestnut blight.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Cryphonectria Target entity description: Cryphonectria is a genus of plant-pathogenic fungi best known for containing the species that causes chestnut blight.
-
A.
Nectria
Nectria is a genus of fungi in the order Hypocreales, many species of which are known as plant pathogens causing cankers and other diseases on trees and crops.
-
B.
Ophiostoma
Ophiostoma is a genus of fungi best known for containing species that cause Dutch elm disease in elm trees.
-
C.
Ophiostoma piceae
Ophiostoma piceae is a species of sap-staining fungus commonly associated with coniferous trees and known for causing blue stain in lumber.
-
D.
Ceratocystis
Ceratocystis is a genus of plant-pathogenic fungi known for causing wilt and canker diseases in a wide range of trees and crops.
-
E.
Raffaelea
Raffaelea is a genus of fungi known for its symbiotic associations with bark beetles and its role in causing plant diseases such as laurel wilt.
- F. None of above. chosen
Provenance (5 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_69c008db906c819096f3597d55d95432 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0687f5c6c81909c835329c996b311 |
completed | March 22, 2026, 10:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6388f42648190adbc2d1c1efa75a5 |
completed | March 27, 2026, 7:58 a.m. |
| NEDg | Description generation | batch_69c63c5d5e2881908a27021616c69b97 |
completed | March 27, 2026, 8:14 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c63cb876788190a26ae84c2c69df95 |
completed | March 27, 2026, 8:15 a.m. |
Created at: March 22, 2026, 4:34 p.m.