Triple
T36506698
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Janet Hubert |
E899483
|
entity |
| Predicate | seasonCountOnTheFreshPrinceOfBelAir |
P2652
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [Janet Hubert, seasonCountOnTheFreshPrinceOfBelAir, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: seasonCountOnTheFreshPrinceOfBelAir Context triple: [Janet Hubert, seasonCountOnTheFreshPrinceOfBelAir, 3]
-
A.
numberOfSeasons
chosen
Indicates the total count of seasons associated with a particular entity (such as a series, competition, or event).
-
B.
franchiseSeasonNumber
Indicates the specific season number assigned to an installment within a larger franchise series.
-
C.
playedMoreThanTenSeasonsIn
Indicates that an entity participated as a player in a particular league, team, or competition for more than ten seasons.
-
D.
centuriesInSeason
Indicates the number of centuries (scores of 100 or more runs) achieved by a player during a specific season.
-
E.
seasonNumber
Indicates the ordinal position of a season within a series or sequence of seasons.
- 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_69f76e5b92088190933afda3f7531dd4 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fd6dbd1b648190b1a0b391c03aebc5 |
completed | May 8, 2026, 4:59 a.m. |
| PD | Predicate disambiguation | batch_69fd6a9020548190bbfa845360ac85fb |
completed | May 8, 2026, 4:46 a.m. |
Created at: May 3, 2026, 4:10 p.m.