Triple
T32857674
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Middlesex Health |
E840422
|
entity |
| Predicate | hasMainHospital |
P50261
|
FINISHED |
| Object | Middlesex Hospital |
—
|
NE NERFINISHED |
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: Middlesex Hospital | Statement: [Middlesex Health, hasMainHospital, Middlesex Hospital]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMainHospital Context triple: [Middlesex Health, hasMainHospital, Middlesex Hospital]
-
A.
hasHospitalType
Indicates that a hospital is classified as belonging to a specific type or category (e.g., general, specialized, teaching).
-
B.
containsHospital
chosen
Indicates that one entity includes or encompasses a hospital within its boundaries or composition.
-
C.
hasAffiliatedHospital
Indicates that one entity (typically a medical professional, clinic, or organization) is formally connected or associated with a particular hospital for professional or operational purposes.
-
D.
majorHospital
Indicates that a hospital holds a primary or leading status within a healthcare system or region, typically due to its size, capacity, or range of services.
-
E.
hasMedicalCenter
Indicates that an entity possesses, hosts, or is associated with a medical center facility.
- 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_69f34942465c819099b3fb47f9044f58 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a00ae638fcc819096537b2c21366161 |
completed | May 10, 2026, 4:12 p.m. |
| PD | Predicate disambiguation | batch_6a00ae0551988190bcb3564ed9af2847 |
completed | May 10, 2026, 4:10 p.m. |
Created at: May 1, 2026, 1:17 a.m.