Triple
T27102617
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taran Noah Smith |
E686480
|
entity |
| Predicate | numberOfSeasonsOnHomeImprovement |
P196721
|
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: [Taran Noah Smith, numberOfSeasonsOnHomeImprovement, 8]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfSeasonsOnHomeImprovement Context triple: [Taran Noah Smith, numberOfSeasonsOnHomeImprovement, 8]
-
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.
appearsInTelevisionSeasonCount
chosen
Indicates the number of television seasons in which the subject appears.
-
D.
numberOfEpisodes
Indicates the total count of episodes associated with a given entity, such as a series or season.
-
E.
originalChannelNumberOfSeasons
Indicates the number of seasons that were originally broadcast on a given channel.
- 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_69ef1489f8b481908e24a1985982bd26 |
completed | April 27, 2026, 7:47 a.m. |
| NER | Named-entity recognition | batch_69fe87b609888190913b0c3f787ecdba |
completed | May 9, 2026, 1:02 a.m. |
| PD | Predicate disambiguation | batch_69fe8731af48819092084f6f74bf052d |
completed | May 9, 2026, 1 a.m. |
Created at: April 27, 2026, 8:48 a.m.