Triple
T19876243
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Archie Graham |
E477643
|
entity |
| Predicate | hasFictionalProfessionLocation |
P76778
|
FINISHED |
| Object | small-town Minnesota doctor |
—
|
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: small-town Minnesota doctor | Statement: [Archie Graham, hasFictionalProfessionLocation, small-town Minnesota doctor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalProfessionLocation Context triple: [Archie Graham, hasFictionalProfessionLocation, small-town Minnesota doctor]
-
A.
hasFictionalLocation
Indicates that an entity is associated with, set in, or takes place within a location that exists only in fiction rather than in the real world.
-
B.
workLocationOfFictionalCharacter
chosen
Indicates the place or organization where a fictional character is depicted as working within their narrative context.
-
C.
worksAtFictionalPlace
Indicates that an entity is employed at or associated with performing work in a fictional or imaginary location.
-
D.
hasBranchInFictionalLocation
Indicates that an organization maintains a branch, office, or presence within a fictional or imaginary location.
-
E.
residesInFictionalLocation
Indicates that an entity lives or is based in a location that is explicitly fictional or imaginary.
- 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_69d8e51f32b08190b3687f4f60353250 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e658db058c8190b7bf0b003ead5bfc |
completed | April 20, 2026, 4:48 p.m. |
| PD | Predicate disambiguation | batch_69e537e8c4e481909fe95d795b4864e7 |
completed | April 19, 2026, 8:15 p.m. |
Created at: April 10, 2026, 1:52 p.m.