Triple
T245831
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Best Fancast |
E5034
|
entity |
| Predicate | fandomFocus |
P8696
|
FINISHED |
| Object | science fiction |
—
|
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: science fiction | Statement: [Best Fancast, fandomFocus, science fiction]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fandomFocus Context triple: [Best Fancast, fandomFocus, science fiction]
-
A.
fictionalUniverse
Indicates that two entities exist within, or are associated with, the same fictional universe or narrative setting.
-
B.
fareMedia
Indicates that a particular type of ticket, pass, or payment instrument is used as the medium for paying a fare.
-
C.
hasMediaFranchise
Indicates that one entity is part of, or belongs to, a larger media franchise represented by another entity.
-
D.
popularizedBy
Indicates that something became widely known, accepted, or fashionable as a result of the influence or actions of a particular agent.
-
E.
popularizedIn
Indicates that something became widely known, accepted, or fashionable within a particular place, time period, or context.
- 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_69a257c4bf688190a46ebbf411ab7473 |
completed | Feb. 28, 2026, 2:49 a.m. |
| NER | Named-entity recognition | batch_69a25d128c0081909908825b302ae635 |
completed | Feb. 28, 2026, 3:12 a.m. |
| PD | Predicate disambiguation | batch_69a25b63b0bc8190864d7324d339fb48 |
completed | Feb. 28, 2026, 3:05 a.m. |
| PDg | Predicate description generation | batch_69a25c2ca46c81908c61696f31e59a98 |
completed | Feb. 28, 2026, 3:08 a.m. |
Created at: Feb. 28, 2026, 2:54 a.m.