Triple
T33025687
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Adventure of the Blanched Soldier |
E845035
|
entity |
| Predicate | hasMedicalElement |
P76100
|
FINISHED |
| Object | Hansen's disease (leprosy) |
—
|
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: Hansen's disease (leprosy) | Statement: [The Adventure of the Blanched Soldier, hasMedicalElement, Hansen's disease (leprosy)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMedicalElement Context triple: [The Adventure of the Blanched Soldier, hasMedicalElement, Hansen's disease (leprosy)]
-
A.
usesMedicalDevice
Indicates that one entity employs or operates a medical device in relation to another entity or context.
-
B.
hasPatient
Indicates that an action, event, or process involves a specific entity as the one undergoing or receiving its effects (the patient).
-
C.
hasMedicalCenter
Indicates that an entity possesses, hosts, or is associated with a medical center facility.
-
D.
hasAssociatedDisease
chosen
Indicates that an entity is linked to, or commonly occurs with, a particular disease or medical condition.
-
E.
hasHealthCareCharacteristic
Indicates that an entity possesses a specific healthcare-related attribute, quality, or feature.
- 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_69f34950749c8190ae05cd27adb16d58 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69feba0f09508190b3e871c62b19ec7f |
completed | May 9, 2026, 4:37 a.m. |
| PD | Predicate disambiguation | batch_69feb957fe7c8190969fb31a6d1a59c8 |
completed | May 9, 2026, 4:34 a.m. |
Created at: May 1, 2026, 1:23 a.m.