Triple
T4664824
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Onge |
E102818
|
entity |
| Predicate | healthConcerns |
P4720
|
FINISHED |
| Object | susceptibility to introduced diseases |
—
|
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: susceptibility to introduced diseases | Statement: [Onge, healthConcerns, susceptibility to introduced diseases]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: healthConcerns Context triple: [Onge, healthConcerns, susceptibility to introduced diseases]
-
A.
hasHealthConcern
chosen
Indicates that an entity has a specific health-related issue, condition, or concern associated with it.
-
B.
raisedConcernAbout
Indicates that one entity has expressed worry, doubt, or objection regarding another entity or issue.
-
C.
healthEffect
Indicates the impact or consequence that one entity has on the health or well-being of another.
-
D.
concernsRight
Indicates that something is about or relates specifically to a legal or moral right held by an entity.
-
E.
healthIndicator
Indicates a measure or signal that reflects the health status or condition of an entity.
- 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_69bd43d9cba4819086c1ab1c2d9d2133 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd655aceb081908100ffc0498fe183 |
completed | March 20, 2026, 3:18 p.m. |
| PD | Predicate disambiguation | batch_69bd6215864c8190b50ba0f63ba87d0c |
completed | March 20, 2026, 3:04 p.m. |
Created at: March 20, 2026, 1:15 p.m.