Triple
T15225682
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Accelerator |
E363871
|
entity |
| Predicate | hasTrack |
P3284
|
FINISHED |
| Object | Another Year |
E366029
|
NE 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: Another Year | Statement: [Accelerator, hasTrack, Another Year]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Another Year Context triple: [Accelerator, hasTrack, Another Year]
-
A.
Another Year
chosen
Another Year is a 2010 British drama film directed by Mike Leigh that follows a contented middle-aged couple and their troubled friends over the course of four seasons.
-
B.
The Years
The Years is a 1937 novel by Virginia Woolf that traces the changing fortunes of the Pargiter family across several decades, blending social history with experimental narrative form.
-
C.
A Year and a Day
A Year and a Day is a film featuring actor T. R. Knight in its cast.
-
D.
45 Years
45 Years is a British drama film about a couple whose marriage is tested in the week leading up to their 45th wedding anniversary.
-
E.
Das Jahr
"Das Jahr" is a cycle of twelve character pieces for piano by Fanny Hensel, each depicting a month of the year and often considered her most significant large-scale piano work.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d85a0ce24c81909c4d3b6475548c95 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0078bb32881909927561c6c072546 |
completed | April 15, 2026, 9:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fedd35ae348190beb1b113bfc66ab3 |
completed | May 9, 2026, 7:07 a.m. |
Created at: April 10, 2026, 3:12 a.m.