Triple
T36233330
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Spring Split |
E891307
|
entity |
| Predicate | oftenDetermines |
P195706
|
FINISHED |
| Object | international event qualifiers |
—
|
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: international event qualifiers | Statement: [Spring Split, oftenDetermines, international event qualifiers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oftenDetermines Context triple: [Spring Split, oftenDetermines, international event qualifiers]
-
A.
oftenDeterministicDuring
Indicates that one entity tends to behave or occur in a predictable, rule-governed way during the time, process, or condition specified by another entity.
-
B.
oftenDescribes
Indicates that one entity is frequently used to characterize, depict, or provide information about another entity.
-
C.
oftenFrom
Indicates that something frequently originates, derives, or comes from a particular source or location.
-
D.
oftenHave
Indicates that one entity frequently possesses, experiences, or is associated with another entity.
-
E.
oftenSetIn
Indicates that something, such as a story or event, frequently takes place within a particular setting or context.
- 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_69f76e4387048190a1b27bcbf4ec7423 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fddf721c1481909301a0f379368f10 |
completed | May 8, 2026, 1:04 p.m. |
| PD | Predicate disambiguation | batch_69fddda1ae7c8190b5848ff9a9e39826 |
completed | May 8, 2026, 12:57 p.m. |
| PDg | Predicate description generation | batch_69fddf70ab10819088b76bd98e208354 |
completed | May 8, 2026, 1:04 p.m. |
Created at: May 3, 2026, 4:09 p.m.