Triple
T19504932
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Russian Doll |
E487997
|
entity |
| Predicate | firstSeasonEpisodeCount |
P102411
|
FINISHED |
| Object | 8 |
—
|
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: 8 | Statement: [Russian Doll, firstSeasonEpisodeCount, 8]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstSeasonEpisodeCount Context triple: [Russian Doll, firstSeasonEpisodeCount, 8]
-
A.
numberOfEpisodes
Indicates the total count of episodes associated with a given entity, such as a series or season.
-
B.
hasEpisodeCountInFirstSeries
chosen
Indicates that an entity has a specific number of episodes in its first series or season.
-
C.
numberOfSeasons
Indicates the total count of seasons associated with a particular entity (such as a series, competition, or event).
-
D.
firstSeasonOf
Indicates that one entity is the first season installment belonging to the series or show represented by the other entity.
-
E.
firstAiredInSeason
Indicates the specific season of a series in which an episode or content item was originally first broadcast or released.
- 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_69d8e8d9d1c88190b01cd78b8be49384 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e635113fdc819098ea0f738d01925c |
completed | April 20, 2026, 2:15 p.m. |
| PD | Predicate disambiguation | batch_69e4fd7bd25881908caa04eaef1f6718 |
completed | April 19, 2026, 4:06 p.m. |
Created at: April 10, 2026, 1:40 p.m.