Triple
T3768746
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UCI World Ranking |
E82744
|
entity |
| Predicate | temporalStructure |
P25625
|
FINISHED |
| Object | season-long |
—
|
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: season-long | Statement: [UCI World Ranking, temporalStructure, season-long]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: temporalStructure Context triple: [UCI World Ranking, temporalStructure, season-long]
-
A.
temporalAspect
Indicates the time-related characteristics or phase (such as duration, frequency, or temporal status) associated with an event or relationship.
-
B.
temporalRelation
Indicates a relationship that specifies how two events or states are positioned relative to each other in time (e.g., before, after, or overlapping).
-
C.
timeStructure
chosen
Indicates that one entity defines, constrains, or organizes the temporal framework or schedule within which another entity exists or operates.
-
D.
temporalEffect
Indicates a relationship where one event, state, or action produces consequences or changes that occur at a later time.
-
E.
segmentStructure
Indicates that one entity represents a structural or organizational subdivision (a segment) within the overall structure of another entity.
- 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_69ad8b207b0081909d2b48843fbd8795 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcc2d4b848190bf63fb3ed5d3b2d9 |
completed | March 8, 2026, 7:21 p.m. |
| PD | Predicate disambiguation | batch_69adc04ec36c8190bd5b944d4f4d32aa |
completed | March 8, 2026, 6:30 p.m. |
Created at: March 8, 2026, 3:35 p.m.