Triple
T34098741
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | No Agenda |
E874505
|
entity |
| Predicate | approximateEpisodeCount |
P2593
|
FINISHED |
| Object | over 1500 episodes |
—
|
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: over 1500 episodes | Statement: [No Agenda, approximateEpisodeCount, over 1500 episodes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateEpisodeCount Context triple: [No Agenda, approximateEpisodeCount, over 1500 episodes]
-
A.
numberOfEpisodes
chosen
Indicates the total count of episodes associated with a given entity, such as a series or season.
-
B.
segmentCountPerEpisode
Indicates the number of distinct segments contained within a single episode.
-
C.
partOfEpisodeCount
Indicates that one entity specifies the number of episodes contained within another entity (such as a season, series, or collection).
-
D.
appearsInEpisodeCountType
Indicates the type or category used to quantify how many episodes an entity appears in.
-
E.
hasNumberOfEPs
Indicates the quantity or count of EPs (e.g., episodes, extended plays, or similar units) associated with an entity.
- 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_69f349a735208190a1dbfb1c2a121059 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69ff0d80c0dc81909fbd12285c7a45c0 |
completed | May 9, 2026, 10:33 a.m. |
| PD | Predicate disambiguation | batch_69ff0cd03e78819094895058f925fbfa |
completed | May 9, 2026, 10:30 a.m. |
Created at: May 1, 2026, 1:53 a.m.