Triple
T32637270
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tyler Hughes |
E834376
|
entity |
| Predicate | fictionalUniverseWorkType |
P195941
|
FINISHED |
| Object | television series |
—
|
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: television series | Statement: [Tyler Hughes, fictionalUniverseWorkType, television series]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fictionalUniverseWorkType Context triple: [Tyler Hughes, fictionalUniverseWorkType, television series]
-
A.
fictionalUniverse
Indicates that two entities exist within, or are associated with, the same fictional universe or narrative setting.
-
B.
fictionalUniverseRelation
Indicates a relationship between entities based on their connection to the same or related fictional universes, such as shared settings, continuities, or crossover worlds.
-
C.
hasFictionalUniverseType
Indicates that an entity is associated with, or belongs to, a particular type or category of fictional universe.
-
D.
hasFictionalUniverseProperty
Indicates that a fictional universe possesses a specific characteristic, attribute, or property.
-
E.
fictionalUniverseCreated
Indicates that one entity is the creator or originator of a particular fictional universe or setting in which stories or works take place.
- F. None of above. chosen
Provenance (4 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_69f3492dc2308190a88c6e30a3f3f576 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fdf5d05cc481909ec9e1b1f0784279 |
completed | May 8, 2026, 2:40 p.m. |
| PD | Predicate disambiguation | batch_69fdf0cdd6948190838864ab3120dfa6 |
completed | May 8, 2026, 2:18 p.m. |
| PDg | Predicate description generation | batch_69fdf5cfa1ec8190b80d887fa1bfb4cf |
completed | May 8, 2026, 2:40 p.m. |
Created at: May 1, 2026, 1:07 a.m.