Triple
T10825556
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Qikiqtani General Hospital |
E255489
|
entity |
| Predicate | hasLaboratoryServices |
P95935
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Qikiqtani General Hospital, hasLaboratoryServices, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLaboratoryServices Context triple: [Qikiqtani General Hospital, hasLaboratoryServices, yes]
-
A.
hasLaboratorySystem
Indicates that one entity possesses, uses, or is associated with a particular laboratory system.
-
B.
hasKeyLaboratory
Indicates that an entity possesses or is associated with a designated key laboratory, typically as an important research or development facility under its responsibility.
-
C.
laboratoryAnalysis
Indicates that a sample or material is being examined, tested, or measured using scientific procedures in a laboratory setting.
-
D.
hasClinicalService
Indicates that an entity provides, offers, or is associated with a specific clinical service.
-
E.
laboratoryModule
Indicates a relationship where an entity is a laboratory module or functions as a lab-specific component or unit within a larger system or structure.
- F. None of above. chosen
Provenance (4 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_69d6aa8081448190a9324184f2bd1c26 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d734d0389c819090a892693c4046ed |
completed | April 9, 2026, 5:10 a.m. |
| PD | Predicate disambiguation | batch_69d70d1bf3648190b36fa96ea018e0dc |
completed | April 9, 2026, 2:21 a.m. |
| PDg | Predicate description generation | batch_69d7101c96708190808fef73199e8482 |
completed | April 9, 2026, 2:34 a.m. |
Created at: April 8, 2026, 9:19 p.m.