Triple
T4136925
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chernobyl disaster |
E85175
|
entity |
| Predicate | longTermHealthConcern |
P4720
|
FINISHED |
| Object | thyroid cancer in exposed children |
—
|
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: thyroid cancer in exposed children | Statement: [Chernobyl disaster, longTermHealthConcern, thyroid cancer in exposed children]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: longTermHealthConcern Context triple: [Chernobyl disaster, longTermHealthConcern, thyroid cancer in exposed children]
-
A.
hasHealthConcern
chosen
Indicates that an entity has a specific health-related issue, condition, or concern associated with it.
-
B.
focusesOnMedicalCare
Indicates that one entity directs attention, resources, or activity specifically toward providing or improving medical care for another entity.
-
C.
healthEffect
Indicates the impact or consequence that one entity has on the health or well-being of another.
-
D.
healthIndicator
Indicates a measure or signal that reflects the health status or condition of an entity.
-
E.
durationOfAffliction
Indicates the length of time that an affliction or condition persists for 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_69aed935ccd881909dc61f81bcdb7a78 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af03a0f3408190adba7a8513bd3d12 |
completed | March 9, 2026, 5:30 p.m. |
| PD | Predicate disambiguation | batch_69af018a54848190987f18c066c75068 |
completed | March 9, 2026, 5:21 p.m. |
Created at: March 9, 2026, 3:43 p.m.