Triple
T8578293
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Penn & Teller: Bullshit! |
E203103
|
entity |
| Predicate | notableEpisodeTopics |
P82948
|
FINISHED |
| Object | astrology |
—
|
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: astrology | Statement: [Penn & Teller: Bullshit!, notableEpisodeTopics, astrology]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableEpisodeTopics Context triple: [Penn & Teller: Bullshit!, notableEpisodeTopics, astrology]
-
A.
notableEpisode
Indicates that a particular episode is especially significant, memorable, or noteworthy in relation to the subject.
-
B.
notableEP
Indicates that an entity is especially well-known or significant for a particular EP (extended play recording).
-
C.
notableEpisodeCount
Indicates the number of episodes in which the subject is notably featured or recognized.
-
D.
notableShow
Indicates that a show is especially prominent, distinguished, or significant in some noteworthy way.
-
E.
notableSeries
Indicates that an entity is a significant or well-known installment within a particular series or franchise.
- 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_69ca8328ebe481909a8c038fa79959b4 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbea989bec81909b8c8b4af7c568ff |
completed | March 31, 2026, 3:39 p.m. |
| PD | Predicate disambiguation | batch_69cbd11b13108190b07f8f161425a585 |
completed | March 31, 2026, 1:50 p.m. |
| PDg | Predicate description generation | batch_69cbe12dd0b88190a38ec4d15dcc870b |
completed | March 31, 2026, 2:58 p.m. |
Created at: March 30, 2026, 6:22 p.m.