Triple
T31712187
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | San DiFrangeles |
E809355
|
entity |
| Predicate | settingForCharacterGroup |
P183518
|
FINISHED |
| Object | doctors at Sacred Heart Hospital |
—
|
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: doctors at Sacred Heart Hospital | Statement: [San DiFrangeles, settingForCharacterGroup, doctors at Sacred Heart Hospital]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: settingForCharacterGroup Context triple: [San DiFrangeles, settingForCharacterGroup, doctors at Sacred Heart Hospital]
-
A.
associatedWithCharacterGroup
Indicates that an entity has a connection or affiliation with a particular group of characters.
-
B.
hasCharacterGroupName
Indicates that an entity is associated with a specific name identifying a group of characters.
-
C.
titleCharacterGroup
Indicates that a group of characters is associated with or featured in the title of a work.
-
D.
settingOfRole
Indicates the context, environment, or situation in which a particular role is performed or holds relevance.
-
E.
characterAssignmentPolicy
Indicates the rules or criteria governing how characters are assigned or allocated to specific roles, positions, or entities.
- 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_69f348df4e048190a4a5a9932ada78d6 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f7a01efcc08190bba489a9099b8684 |
completed | May 3, 2026, 7:21 p.m. |
| PD | Predicate disambiguation | batch_69f79e4888248190be2f63cdfb5cd7b7 |
completed | May 3, 2026, 7:13 p.m. |
| PDg | Predicate description generation | batch_69f79f477c4c8190a35cb6d87b1dcbd1 |
completed | May 3, 2026, 7:17 p.m. |
Created at: April 30, 2026, 11:16 p.m.