Triple
T38242025
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chastain Park Memorial Hospital |
E1013790
|
entity |
| Predicate | hasOnScreenOwnershipChanges |
P193233
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Chastain Park Memorial Hospital, hasOnScreenOwnershipChanges, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOnScreenOwnershipChanges Context triple: [Chastain Park Memorial Hospital, hasOnScreenOwnershipChanges, true]
-
A.
hasOnScreenOwner
Indicates that an entity is owned or controlled by another entity that is explicitly shown or represented on screen.
-
B.
hasOnScreenEvents
Indicates that certain events occur or are presented visibly on a screen or display.
-
C.
hasOnScreenOccupation
Indicates that an entity is depicted as having a particular occupation or job within an on-screen context (e.g., in a film, TV show, or other visual media).
-
D.
hasOnscreenFunction
Indicates that an entity serves a particular role or performs a specific function when it appears on screen.
-
E.
hasOnScreenResidence
Indicates that an entity has a residence or home that is depicted or shown on screen within a visual work.
- 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_69f76dd72a248190a5fe18db2bd1eb15 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fd3a69f1e08190a11aed015bff0858 |
completed | May 8, 2026, 1:20 a.m. |
| PD | Predicate disambiguation | batch_69fd39124180819080ca7911d3515d6d |
completed | May 8, 2026, 1:14 a.m. |
| PDg | Predicate description generation | batch_69fd3a6905b88190ae12b43576f4cc63 |
completed | May 8, 2026, 1:20 a.m. |
Created at: May 3, 2026, 4:30 p.m.