Triple
T32020881
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jennifer Dylan Turk |
E817685
|
entity |
| Predicate | birthPlaceInStory |
P49113
|
FINISHED |
| Object | Sacred Heart Hospital |
—
|
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: Sacred Heart Hospital | Statement: [Jennifer Dylan Turk, birthPlaceInStory, Sacred Heart Hospital]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: birthPlaceInStory Context triple: [Jennifer Dylan Turk, birthPlaceInStory, Sacred Heart Hospital]
-
A.
homeLocationInStory
Indicates the place that serves as a character’s primary home or base of residence within the context of the story.
-
B.
birthPlaceAccordingTo
Indicates that an entity’s place of birth is given as a specific location according to a particular source or authority.
-
C.
fictionalBirthPlace
chosen
Indicates the fictional location where a character or entity is described as having been born within a narrative or imagined context.
-
D.
homeCityInStory
Indicates that a specified city serves as a character’s home city within the context of a particular story.
-
E.
placeOfUpbringing
Indicates the location where an individual was raised or spent most of their formative years.
- 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_69f348fb04e4819081f4eab040ed7959 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6b466aaa08190bcafc15b3b2d3d31 |
completed | May 3, 2026, 2:35 a.m. |
| PD | Predicate disambiguation | batch_69f6b151ad008190836c1bcdec503ce2 |
completed | May 3, 2026, 2:22 a.m. |
Created at: May 1, 2026, 12:16 a.m.