Triple
T25093877
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Best American Short Stories 2008 |
E628534
|
entity |
| Predicate | seriesFrequency |
P160844
|
FINISHED |
| Object | annual |
—
|
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: annual | Statement: [The Best American Short Stories 2008, seriesFrequency, annual]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: seriesFrequency Context triple: [The Best American Short Stories 2008, seriesFrequency, annual]
-
A.
serviceFrequencyType
Indicates how often a service occurs or is scheduled within a given time period.
-
B.
serviceFrequencyContext
Indicates the contextual conditions or circumstances under which a service’s frequency is defined, applied, or interpreted.
-
C.
broadcastFrequencyType
Indicates the type or category of frequency used for broadcasting a signal or transmission.
-
D.
broadcastFrequency
Indicates the specific radio or transmission frequency at which a broadcast is sent or received.
-
E.
hasSeasonFrequency
Indicates how often something occurs or is scheduled within a specific season.
- 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_69e2ff2f58e881908340527bc5d34f07 |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f60ac643108190ae81561267155791 |
completed | May 2, 2026, 2:31 p.m. |
| PD | Predicate disambiguation | batch_69f602ce79ec8190b8336c2b9de18ac7 |
completed | May 2, 2026, 1:57 p.m. |
| PDg | Predicate description generation | batch_69f606c15af88190958856a9e467b826 |
completed | May 2, 2026, 2:14 p.m. |
Created at: April 18, 2026, 6:24 a.m.