Triple
T24430311
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brenda Song as Veronica |
E615985
|
entity |
| Predicate | partOfSeasonCount |
P156092
|
FINISHED |
| Object | 1 |
—
|
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: 1 | Statement: [Brenda Song as Veronica, partOfSeasonCount, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: partOfSeasonCount Context triple: [Brenda Song as Veronica, partOfSeasonCount, 1]
-
A.
numberOfSeasons
Indicates the total count of seasons associated with a particular entity (such as a series, competition, or event).
-
B.
numberOfSeriesPerSeason
Indicates the total count of series (or episodes/instalments) that occur within a single season of something.
-
C.
seasonNumber
Indicates the ordinal position of a season within a series or sequence of seasons.
-
D.
franchiseSeasonNumber
Indicates the specific season number assigned to an installment within a larger franchise series.
-
E.
seasonCountDetail
Indicates the specific number of seasons associated with something, often including additional contextual details about that season count.
- 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_69e2d7eadb248190a867130fe45f0388 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f296aab8948190b9cb869bab71fb4c |
completed | April 29, 2026, 11:39 p.m. |
| PD | Predicate disambiguation | batch_69f287d3237c819099559c00f83131d8 |
completed | April 29, 2026, 10:36 p.m. |
| PDg | Predicate description generation | batch_69f28f4d978c81908310c01def2514cc |
completed | April 29, 2026, 11:07 p.m. |
Created at: April 18, 2026, 2:16 a.m.