Triple
T27088822
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seattle Grace |
E686104
|
entity |
| Predicate | associatedWithFictionalHospital |
P46057
|
FINISHED |
| Object | Mercy West Medical Center |
—
|
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: Mercy West Medical Center | Statement: [Seattle Grace, associatedWithFictionalHospital, Mercy West Medical Center]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithFictionalHospital Context triple: [Seattle Grace, associatedWithFictionalHospital, Mercy West Medical Center]
-
A.
fictionalHospital
chosen
Indicates that a hospital is imaginary or exists only within a fictional or narrative context, rather than in reality.
-
B.
hasFictionalClinic
Indicates that an entity is associated with or contains a clinic that exists only in a fictional or imaginary context.
-
C.
associatedWithFictionalEvent
Indicates that an entity has a connection or involvement with a fictional event, such as being based on, inspired by, or participating in that imagined occurrence.
-
D.
hasFictionalEmergencyRoom
Indicates that an entity includes or features a fictional emergency room as part of its setting or content.
-
E.
worksAtHospital
Indicates that a person is employed at and performs their professional duties in a hospital.
- 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_69ef148940ec819097b5c20fbfbf7c81 |
completed | April 27, 2026, 7:47 a.m. |
| NER | Named-entity recognition | batch_69ffb1f0b03c81909ddb81f07ce74e88 |
completed | May 9, 2026, 10:15 p.m. |
| PD | Predicate disambiguation | batch_69ffb1662b2481908582e0612744f4c5 |
completed | May 9, 2026, 10:12 p.m. |
Created at: April 27, 2026, 8:39 a.m.