Triple
T30253472
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1950 French Annapurna expedition |
E769271
|
entity |
| Predicate | medicalConsequencesForMembers |
P4720
|
FINISHED |
| Object | severe frostbite |
—
|
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: severe frostbite | Statement: [1950 French Annapurna expedition, medicalConsequencesForMembers, severe frostbite]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: medicalConsequencesForMembers Context triple: [1950 French Annapurna expedition, medicalConsequencesForMembers, severe frostbite]
-
A.
medicalConditionCarrier
Indicates that an entity carries or harbors a specific medical condition (often genetically or asymptomatically) that can potentially be transmitted or inherited.
-
B.
hasHealthConcern
chosen
Indicates that an entity has a specific health-related issue, condition, or concern associated with it.
-
C.
medicalConditionCovered
Indicates that a specified medical condition is included under the scope of coverage provided by a particular healthcare plan, policy, or service.
-
D.
medicalCoverageAfter
Indicates that one entity’s medical insurance coverage begins or applies after the time, event, or coverage period associated with another entity.
-
E.
isMedicallyRelevant
Indicates that something has significance, impact, or applicability within a medical or clinical context.
- 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_69f224831dc08190b2e569b987264057 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f6807d23cc819094279e32d55ea1b8 |
completed | May 2, 2026, 10:53 p.m. |
| PD | Predicate disambiguation | batch_69f6760216108190bbb708d53a6c2c25 |
completed | May 2, 2026, 10:09 p.m. |
Created at: April 29, 2026, 7:40 p.m.