Triple
T288196
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CEST |
E5930
|
entity |
| Predicate | typicalEnd |
P3188
|
FINISHED |
| Object | last Sunday in October |
—
|
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: last Sunday in October | Statement: [CEST, typicalEnd, last Sunday in October]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalEnd Context triple: [CEST, typicalEnd, last Sunday in October]
-
A.
typicalTimes
Indicates the usual or characteristic times at which an event, activity, or condition typically occurs.
-
B.
typicalConclusion
Indicates that one entity is the usual or expected outcome, result, or ending that follows from another entity or situation.
-
C.
typicalSchedule
Indicates the usual or standard timing and sequence of activities or events associated with an entity.
-
D.
seasonTypicalEndMonth
chosen
Indicates the month in which a given season typically ends.
-
E.
typicalEvent
Indicates that the associated event is a common, characteristic, or prototypical occurrence for the given entity or situation.
- 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_69a25946a7ac8190a78871c210213272 |
completed | Feb. 28, 2026, 2:56 a.m. |
| NER | Named-entity recognition | batch_69a25e2f5c0081908e548b314f5e986d |
completed | Feb. 28, 2026, 3:17 a.m. |
| PD | Predicate disambiguation | batch_69a25b7c1448819082064f474633acd5 |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 3:02 a.m.