Triple
T15633045
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Children's Mercy Hospital |
E375866
|
entity |
| Predicate | hasAgeRangeOfPatients |
P2736
|
FINISHED |
| Object | 0-18 years |
—
|
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: 0-18 years | Statement: [Children's Mercy Hospital, hasAgeRangeOfPatients, 0-18 years]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAgeRangeOfPatients Context triple: [Children's Mercy Hospital, hasAgeRangeOfPatients, 0-18 years]
-
A.
containsAge
Indicates that one entity includes or specifies the age value or age-related information of another entity.
-
B.
ageRange
chosen
Indicates the span of ages within which an entity or relationship is considered valid or applicable.
-
C.
supportsAgeRange
Indicates that one entity is compatible with, valid for, or designed to accommodate a specified range of ages.
-
D.
typicalEligibilityAge
Indicates the usual or standard age at which an entity qualifies for or becomes eligible for a particular status, benefit, or activity.
-
E.
hasPatientGroup
Indicates a relationship in which an entity (such as a study, treatment, or clinical activity) is associated with a specific group of patients it involves or targets.
- 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_69d85cd035a48190b73d5579ab73969a |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04eb7338881909f3c430bb73f91d1 |
completed | April 16, 2026, 2:51 a.m. |
| PD | Predicate disambiguation | batch_69deda868d4481908f4bce1c64d2902a |
completed | April 15, 2026, 12:23 a.m. |
Created at: April 10, 2026, 4:14 a.m.