Triple
T33913987
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Smallville High School |
E869397
|
entity |
| Predicate | fictionalLocationInState |
P137478
|
FINISHED |
| Object | Kansas |
—
|
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: Kansas | Statement: [Smallville High School, fictionalLocationInState, Kansas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fictionalLocationInState Context triple: [Smallville High School, fictionalLocationInState, Kansas]
-
A.
basedInFictionalLocation
Indicates that an entity’s primary setting, origin, or operations occur in a fictional (non-real) location.
-
B.
stateOfFictionalLocation
chosen
Indicates that a fictional location is situated within or belongs to a particular state or state-like administrative region.
-
C.
fictionalCountryLocation
Indicates that a fictional country is located within, or geographically associated with, a specified place or region.
-
D.
basedInFictionalWorkLocation
Indicates that an entity’s location or setting is situated within a fictional place as depicted in a specific creative work.
-
E.
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.
- 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_69f3499869bc8190b6c33a81686af226 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fe9fb9735c8190a360b556c9d00b3f |
completed | May 9, 2026, 2:45 a.m. |
| PD | Predicate disambiguation | batch_69fe9eaa88008190a9b2a469dc685002 |
completed | May 9, 2026, 2:40 a.m. |
Created at: May 1, 2026, 1:48 a.m.