Triple
T25342821
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MetroWest Medical Center |
E635461
|
entity |
| Predicate | offersDepartment |
P166575
|
FINISHED |
| Object | emergency department |
—
|
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: emergency department | Statement: [MetroWest Medical Center, offersDepartment, emergency department]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offersDepartment Context triple: [MetroWest Medical Center, offersDepartment, emergency department]
-
A.
offeredByDepartment
Indicates that something, such as a course or program, is provided or made available by a specific department.
-
B.
offersProduct
Indicates that one entity makes a product available to another entity, typically for sale or use.
-
C.
offersProductCategory
Indicates that a provider or seller makes products belonging to a specific product category available.
-
D.
supportsDepartment
Indicates that one entity provides assistance, resources, or backing to a specific department.
-
E.
offersServiceIn
Indicates that a provider makes a particular service available within a specified location or jurisdiction.
- 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_69e75a99bd6481909476115b35b9a8e4 |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f662a29b3881909957a7e3b986653c |
completed | May 2, 2026, 8:46 p.m. |
| PD | Predicate disambiguation | batch_69f660eea4648190b0d5e24293607813 |
completed | May 2, 2026, 8:39 p.m. |
| PDg | Predicate description generation | batch_69f661b47d088190934f63884a203261 |
completed | May 2, 2026, 8:42 p.m. |
Created at: April 21, 2026, 1:32 p.m.