Triple
T25414087
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | KCOS |
E636780
|
entity |
| Predicate | associatedDST |
P191075
|
FINISHED |
| Object | observes daylight saving time |
—
|
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: observes daylight saving time | Statement: [KCOS, associatedDST, observes daylight saving time]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedDST Context triple: [KCOS, associatedDST, observes daylight saving time]
-
A.
associatedState
Indicates that one entity is linked or connected to a particular state, condition, or status of another entity.
-
B.
associatedFair
Indicates a relationship where one entity is linked or connected to a particular fair, such as being held at, organized by, or otherwise related to that fair.
-
C.
associatedStable
Indicates that one entity is linked or connected to a particular stable in a way that denotes an ongoing or defined association.
-
D.
associatedThrough
Indicates that two entities are connected or related to each other by means of a specified intermediary, context, or linkage.
-
E.
associatedDam
Indicates a relationship where one entity is linked or connected to a specific dam, typically as its related or corresponding dam structure.
- 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_69e75db4135881909acc287ebcb7a505 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69fcda3699948190adb57625bae08091 |
completed | May 7, 2026, 6:30 p.m. |
| PD | Predicate disambiguation | batch_69fcd8fd16d08190b0aca6e19a632e99 |
completed | May 7, 2026, 6:25 p.m. |
| PDg | Predicate description generation | batch_69fcda35dc048190a3c90e15230900e0 |
completed | May 7, 2026, 6:30 p.m. |
Created at: April 21, 2026, 1:55 p.m.