Triple
T16061267
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2010 FINA Swimming World Cup (Beijing leg) |
E389616
|
entity |
| Predicate | recurringSeries |
P121478
|
FINISHED |
| Object | FINA Swimming World Cup annual circuit |
—
|
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: FINA Swimming World Cup annual circuit | Statement: [2010 FINA Swimming World Cup (Beijing leg), recurringSeries, FINA Swimming World Cup annual circuit]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: recurringSeries Context triple: [2010 FINA Swimming World Cup (Beijing leg), recurringSeries, FINA Swimming World Cup annual circuit]
-
A.
recurringEvent
Indicates that an event occurs repeatedly over time according to some regular pattern or schedule.
-
B.
recurringDuring
Indicates that an event or state happens repeatedly within the time span or context defined by another event or interval.
-
C.
recurrenceType
Indicates the pattern or frequency with which an event or action repeats over time.
-
D.
recurringSegmentOn
Indicates that one entity appears repeatedly as a regular segment or feature within another entity, such as a show, publication, or series.
-
E.
recurringLocation
Indicates that an event, action, or state happens repeatedly at the specified location over time.
- 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_69d86dae698881908327ef2d67706cb9 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1858a00888190b8505071575dc56f |
completed | April 17, 2026, 12:57 a.m. |
| PD | Predicate disambiguation | batch_69e18272f2288190a17d45fb01cc2b07 |
completed | April 17, 2026, 12:44 a.m. |
| PDg | Predicate description generation | batch_69e185879c10819080a18e24969b5a6d |
completed | April 17, 2026, 12:57 a.m. |
Created at: April 10, 2026, 4:57 a.m.