Triple
T18116938
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MedStar Union Memorial Hospital |
E433627
|
entity |
| Predicate | orthopedicCenter |
P130509
|
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: [MedStar Union Memorial Hospital, orthopedicCenter, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: orthopedicCenter Context triple: [MedStar Union Memorial Hospital, orthopedicCenter, yes]
-
A.
hospitalLocation
Indicates the geographic place or address where a hospital is situated.
-
B.
hasMedicalCenter
Indicates that an entity possesses, hosts, or is associated with a medical center facility.
-
C.
designatedAsFlagshipHospitalFor
Indicates that one hospital has been officially selected or recognized as the primary or leading flagship institution for another entity (such as a health system, region, or organization).
-
D.
medicalPractice
Indicates a relationship where an entity engages in or carries out the professional provision of medical care or services.
-
E.
hasTraumaCenter
Indicates that an entity (such as a hospital or facility) includes or is equipped with a designated trauma center capable of providing specialized emergency care for severe injuries.
- 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_69d8b90916008190a1f110bd7ced5473 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4ddd67a2481909d27a4a49b095f8c |
completed | April 19, 2026, 1:51 p.m. |
| PD | Predicate disambiguation | batch_69e43313ca788190baa224269e71de49 |
completed | April 19, 2026, 1:42 a.m. |
| PDg | Predicate description generation | batch_69e438f5ae2c8190b11dee46534fa5a9 |
completed | April 19, 2026, 2:07 a.m. |
Created at: April 10, 2026, 10:28 a.m.