Triple
T32396286
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miranda Bailey |
E827817
|
entity |
| Predicate | worksInFictionalSetting |
P131086
|
FINISHED |
| Object | Seattle |
—
|
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: Seattle | Statement: [Miranda Bailey, worksInFictionalSetting, Seattle]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: worksInFictionalSetting Context triple: [Miranda Bailey, worksInFictionalSetting, Seattle]
-
A.
worksInFictionalContext
chosen
Indicates that an entity performs work or fulfills a role within a fictional or imagined setting rather than in real-world circumstances.
-
B.
basedInFictionalSetting
Indicates that an entity’s primary location or setting exists within a fictional or imaginary world rather than the real world.
-
C.
operatesInFictionalSetting
Indicates that an entity carries out its activities or functions within a fictional or imaginary setting rather than a real-world context.
-
D.
associatedWithFictionalSetting
Indicates that an entity has a connection or relevance to a particular fictional setting or universe.
-
E.
isSetInFictionalUniverse
Indicates that a narrative work takes place within a specific fictional universe or setting.
- 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_69f34919342c8190a4c3bf35a90d4e58 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f7979a073881909a4fde2558e6b6f3 |
completed | May 3, 2026, 6:44 p.m. |
| PD | Predicate disambiguation | batch_69f7961550f88190b7bb8a9155458b54 |
completed | May 3, 2026, 6:38 p.m. |
Created at: May 1, 2026, 12:52 a.m.