Triple
T37808910
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 100 Questions |
E942580
|
entity |
| Predicate | airedEpisodes |
P189238
|
FINISHED |
| Object | 6 |
—
|
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: 6 | Statement: [100 Questions, airedEpisodes, 6]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airedEpisodes Context triple: [100 Questions, airedEpisodes, 6]
-
A.
airedSeries
Indicates that a broadcasting entity transmitted or showed a particular series on air.
-
B.
associatedEpisode
Indicates that one entity is linked or connected to a particular episode as its related or relevant installment.
-
C.
airedAsSeason
Indicates that one or more episodes or segments were broadcast together as a specific television season.
-
D.
intendedEpisodes
Indicates that one entity is planned or designated to appear in, be used for, or be associated with specific episodes of another entity (such as a series or program).
-
E.
hasEpisode
Indicates that something, typically a series or program, includes a specific episode as one of its constituent parts.
- 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_69f76ee8104c8190ab17133ccd8f86e6 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fbb9e8108c8190ae1c7940b1677e95 |
completed | May 6, 2026, 10 p.m. |
| PD | Predicate disambiguation | batch_69fbb141605c8190b9c27d70352522db |
completed | May 6, 2026, 9:23 p.m. |
| PDg | Predicate description generation | batch_69fbb9e69b7481909beaf8264d87c5e5 |
completed | May 6, 2026, 10 p.m. |
Created at: May 3, 2026, 4:19 p.m.