Triple
T18194669
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Swedish football season (spring–autumn) |
E435626
|
entity |
| Predicate | typicalBreaks |
P130179
|
FINISHED |
| Object | winter off-season |
—
|
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: winter off-season | Statement: [Swedish football season (spring–autumn), typicalBreaks, winter off-season]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalBreaks Context triple: [Swedish football season (spring–autumn), typicalBreaks, winter off-season]
-
A.
typicalTimes
Indicates the usual or characteristic times at which an event, activity, or condition typically occurs.
-
B.
typicalSplit
Indicates that something is divided into parts or portions in the usual or most common way.
-
C.
typicalPeriod
Indicates the usual or characteristic time interval or duration associated with an event, process, or state.
-
D.
typicalSchedule
Indicates the usual or standard timing and sequence of activities or events associated with an entity.
-
E.
typicalSegmentType
Indicates that something is classified as belonging to a usual or characteristic type of segment within a broader structure or sequence.
- 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_69d8b90c7ec081909b4694ccecb449c6 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4e0d1eb1c81908c20b6d15e9c4e8e |
completed | April 19, 2026, 2:04 p.m. |
| PD | Predicate disambiguation | batch_69e4331e92408190ad607ba4956a3897 |
completed | April 19, 2026, 1:42 a.m. |
| PDg | Predicate description generation | batch_69e438f684e48190b38c64b58c518b6a |
completed | April 19, 2026, 2:07 a.m. |
Created at: April 10, 2026, 10:31 a.m.