Triple
T23689230
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tilachlidiaceae |
E585252
|
entity |
| Predicate | containsPathogenicSpecies |
P70352
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Tilachlidiaceae, containsPathogenicSpecies, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsPathogenicSpecies Context triple: [Tilachlidiaceae, containsPathogenicSpecies, true]
-
A.
includesPathogensOf
Indicates that one entity contains or encompasses the pathogens that are associated with or originate from another entity.
-
B.
isPathogenOf
Indicates that one entity is a disease-causing agent (pathogen) that infects or causes illness in another entity.
-
C.
pathogenicityToHumans
Indicates that an entity has the capacity to cause disease or harmful health effects in humans.
-
D.
includesSpeciesCausing
chosen
Indicates that one entity contains or encompasses species that are responsible for causing a particular effect, condition, or outcome in another entity.
-
E.
carriesPathogen
Indicates that one entity harbors and can transmit a disease-causing pathogen to another entity or environment.
- 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_69e249037ce0819088b149608e98f685 |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b5c0a218819096c2d174b004c47d |
completed | April 29, 2026, 7:39 a.m. |
| PD | Predicate disambiguation | batch_69f155d5265881908e43a9696b6a6d0f |
completed | April 29, 2026, 12:50 a.m. |
Created at: April 17, 2026, 6:52 p.m.