Triple
T190790
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cairo University Children’s Hospital |
E3715
|
entity |
| Predicate | hasPatientPopulation |
P2750
|
FINISHED |
| Object | infants |
—
|
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: infants | Statement: [Cairo University Children’s Hospital, hasPatientPopulation, infants]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPatientPopulation Context triple: [Cairo University Children’s Hospital, hasPatientPopulation, infants]
-
A.
supportedPopulation
Indicates that one entity provides assistance, resources, or services to sustain or benefit a specified group of people.
-
B.
hasPopulationApproximate
Indicates that an entity has an estimated or approximate population size, rather than an exact count.
-
C.
hasSignificantPopulationGroup
Indicates that an entity contains or is associated with a notable or substantial subgroup of a population, distinguished by shared characteristics or attributes.
-
D.
populationIncludes
chosen
Indicates that a population contains or encompasses the specified individual(s) or subgroup(s) as members or elements.
-
E.
hasPopulationDensity
Indicates the number of individuals (e.g., people, organisms) per unit area associated with a given entity or region.
- 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_69a2548debd48190ae3a06d6e65b53c6 |
completed | Feb. 28, 2026, 2:35 a.m. |
| NER | Named-entity recognition | batch_69a25964fc5c8190bd3e37daaf695ecf |
completed | Feb. 28, 2026, 2:56 a.m. |
| PD | Predicate disambiguation | batch_69a25673ce3c8190b1a3df5b814a0595 |
completed | Feb. 28, 2026, 2:44 a.m. |
Created at: Feb. 28, 2026, 2:41 a.m.