Triple
T29600548
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Františkovy Lázně |
E754428
|
entity |
| Predicate | treatsMedicalConditions |
P88196
|
FINISHED |
| Object | cardiovascular 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: cardiovascular diseases | Statement: [Františkovy Lázně, treatsMedicalConditions, cardiovascular diseases]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: treatsMedicalConditions Context triple: [Františkovy Lázně, treatsMedicalConditions, cardiovascular diseases]
-
A.
treatsConditionType
Indicates that one entity (typically a treatment, procedure, or intervention) is used to address, manage, or cure a particular type or category of medical condition.
-
B.
treats
Indicates that one entity provides medical care or therapeutic intervention to another entity.
-
C.
knownForTreatmentOf
chosen
Indicates that an entity is recognized or notable for providing treatment or medical care for a particular condition, disease, or type of patient.
-
D.
diseaseUsed
Indicates that a particular disease is employed or utilized as a tool, model, or condition within a given context or process.
-
E.
treatmentIndication
Indicates that a treatment is intended to address, alleviate, or prevent a particular condition, symptom, or medical indication.
- 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_69f0ef84e5d08190a0df17f5930ceed3 |
completed | April 28, 2026, 5:33 p.m. |
| NER | Named-entity recognition | batch_69f6a28c7c148190bfc980aad9f678ca |
completed | May 3, 2026, 1:19 a.m. |
| PD | Predicate disambiguation | batch_69f69fe1e3c88190830bb2e9f407357e |
completed | May 3, 2026, 1:07 a.m. |
Created at: April 28, 2026, 6:21 p.m.