Triple
T5930594
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FIFA Women's World Cup Trophy |
E131925
|
entity |
| Predicate | associatedEventFrequency |
P29070
|
FINISHED |
| Object | quadrennial tournament |
—
|
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: quadrennial tournament | Statement: [FIFA Women's World Cup Trophy, associatedEventFrequency, quadrennial tournament]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedEventFrequency Context triple: [FIFA Women's World Cup Trophy, associatedEventFrequency, quadrennial tournament]
-
A.
associatedEventType
Indicates that one entity is linked to another by the type or category of event with which it is associated.
-
B.
hasEventFrequency
chosen
Indicates how often a particular event occurs within a given time period.
-
C.
laterFrequency
Indicates that one event, state, or action occurs with a lower frequency than another in a temporal sequence.
-
D.
performedFrequency
Indicates how often an action or activity is carried out within a given time period.
-
E.
usesFrequency
Indicates that one entity employs or operates another entity at a specified rate, interval, or number of occurrences over time.
- 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_69c0085b75e88190a632f9691f9da48b |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c03c9239e08190bff7ef2bd6d21ae0 |
completed | March 22, 2026, 7:01 p.m. |
| PD | Predicate disambiguation | batch_69c033541d108190a34d1fde2fe9dacb |
completed | March 22, 2026, 6:22 p.m. |
Created at: March 22, 2026, 4 p.m.