Triple
T35253886
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Berkeley Breathed |
E1018170
|
entity |
| Predicate | hasGenreInBloomCounty |
P124610
|
FINISHED |
| Object | political satire |
—
|
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: political satire | Statement: [Berkeley Breathed, hasGenreInBloomCounty, political satire]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGenreInBloomCounty Context triple: [Berkeley Breathed, hasGenreInBloomCounty, political satire]
-
A.
hasGivenGenre
Indicates that an entity is associated with a specific genre that has been assigned or designated to it.
-
B.
hasGenreInSeries
Indicates that a particular genre is associated with, or applies to, a work as it appears within a specific series.
-
C.
hasTargetGenreCategory
Indicates that something is associated with or classified under a specific target genre category.
-
D.
hasGenreOfClaim
Indicates that a claim is categorized or classified under a particular genre or type of claim.
-
E.
hasGenreRelation
chosen
Indicates that there is an association between an entity and a specific genre, specifying the type or category it belongs to.
- 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_69f76de407d081909dfc3c419817ae93 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fda5003cdc8190a558501271389912 |
completed | May 8, 2026, 8:55 a.m. |
| PD | Predicate disambiguation | batch_69fda05bfc2c819096821a5300e9bb24 |
completed | May 8, 2026, 8:35 a.m. |
Created at: May 3, 2026, 4:02 p.m.