Triple
T33974869
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RHINE |
E871107
|
entity |
| Predicate | hasConditionStudied |
P65953
|
FINISHED |
| Object | diabetic macular edema |
—
|
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: diabetic macular edema | Statement: [RHINE, hasConditionStudied, diabetic macular edema]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasConditionStudied Context triple: [RHINE, hasConditionStudied, diabetic macular edema]
-
A.
conditionStudied
chosen
Indicates that a particular condition (e.g., disease, state, or circumstance) is the focus of study or investigation in a given context.
-
B.
hasStudied
Indicates that an entity has engaged in learning or academic work related to another entity (such as a subject, field, or course).
-
C.
hasBeenStudiedFor
Indicates that an entity has been the subject of research, examination, or analysis for a specified purpose, topic, or application.
-
D.
hasStudyType
Indicates that an entity is associated with or characterized by a particular type or design of study.
-
E.
hasBeenStudiedSince
Indicates that an entity has been the subject of study or research starting from a specified point in time and continuing thereafter.
- 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_69f3499da0188190ab1a4ff06fb06a2a |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a037c8ae0248190b7e2ce4bf852c22d |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379f963908190846d232f386fd98f |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:50 a.m.