Triple
T24188302
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cheyenne (TV series) |
E599621
|
entity |
| Predicate | isFictionalUniverseOf |
P15645
|
FINISHED |
| Object | Cheyenne Bodie |
—
|
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: Cheyenne Bodie | Statement: [Cheyenne (TV series), isFictionalUniverseOf, Cheyenne Bodie]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isFictionalUniverseOf Context triple: [Cheyenne (TV series), isFictionalUniverseOf, Cheyenne Bodie]
-
A.
hasFictionalUniverseProperty
Indicates that a fictional universe possesses a specific characteristic, attribute, or property.
-
B.
hasFictionalUniverseType
Indicates that an entity is associated with, or belongs to, a particular type or category of fictional universe.
-
C.
hasFictionalUniverseElement
chosen
Indicates that one entity is a component, feature, or constituent part of the fictional universe represented by the other entity.
-
D.
fictionalUniverse
Indicates that two entities exist within, or are associated with, the same fictional universe or narrative setting.
-
E.
expandsFictionalUniverseOf
Indicates that one work adds new content, details, or dimensions to the fictional universe established by another work.
- 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_69e288cdc8b88190bf2f835d3cb4ca28 |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f27c9ddfcc819096697a844b300cce |
completed | April 29, 2026, 9:48 p.m. |
| PD | Predicate disambiguation | batch_69f1c42f942c8190b103ff29a60fef34 |
completed | April 29, 2026, 8:41 a.m. |
Created at: April 17, 2026, 11:35 p.m.