Triple
T27818005
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Victor Comstock |
E702732
|
entity |
| Predicate | stationFictionalStatus |
P113539
|
FINISHED |
| Object | fictional radio station |
—
|
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: fictional radio station | Statement: [Victor Comstock, stationFictionalStatus, fictional radio station]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: stationFictionalStatus Context triple: [Victor Comstock, stationFictionalStatus, fictional radio station]
-
A.
fictionalStatus
Indicates that an entity exists only in imagination or narrative and does not correspond to a real-world counterpart.
-
B.
stateInFiction
Indicates that a particular state or condition exists within a fictional context or narrative world rather than in real-world actuality.
-
C.
stateOfFictionalLocation
Indicates that a fictional location is situated within or belongs to a particular state or state-like administrative region.
-
D.
hasFictionalTubeStation
chosen
Indicates that an entity features or is associated with a tube (subway) station that exists only in fiction rather than in reality.
-
E.
hasFictionalEstablishmentType
Indicates that an establishment is associated with a particular type or category of fictional setting or institution.
- 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_69ef840ad1e88190b5bff2d1ddec8700 |
completed | April 27, 2026, 3:43 p.m. |
| NER | Named-entity recognition | batch_69f67257b0448190a13011af81c81449 |
completed | May 2, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69f66ec3d3d48190ab2f2b71939e572e |
completed | May 2, 2026, 9:38 p.m. |
Created at: April 27, 2026, 5:46 p.m.