Triple
T23487762
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jacob Jankowski |
E570582
|
entity |
| Predicate | frameNarrativeSetting |
P45019
|
FINISHED |
| Object | nursing home |
—
|
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: nursing home | Statement: [Jacob Jankowski, frameNarrativeSetting, nursing home]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: frameNarrativeSetting Context triple: [Jacob Jankowski, frameNarrativeSetting, nursing home]
-
A.
narrativeSettingOfWork
chosen
Indicates that a particular place, time, or context serves as the narrative setting in which a work’s story or events occur.
-
B.
placeOfSetting
Indicates the location or environment where an event, scene, or situation takes place.
-
C.
narrativeFrame
Indicates the overarching narrative context or perspective within which events, actions, or relationships are presented or interpreted.
-
D.
fictionalStreetSetting
Indicates that an entity is set on or associated with a street that exists only within a fictional or imaginary context.
-
E.
fieldOfNarrative
Indicates that a narrative (such as a story, account, or discourse) is situated within or pertains to a particular field, domain, or area of knowledge or activity.
- 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_69e245b0b01481908f636939bedd804c |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1a7d9cc08819084c532b069f867ee |
completed | April 29, 2026, 6:40 a.m. |
| PD | Predicate disambiguation | batch_69f0620ac3608190b36916261ea50f54 |
completed | April 28, 2026, 7:30 a.m. |
Created at: April 17, 2026, 6:04 p.m.