Triple
T16404338
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | World Table Tennis Championships |
E398385
|
entity |
| Predicate | formerFrequencyChangeYear |
P8725
|
FINISHED |
| Object | 1957 |
—
|
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: 1957 | Statement: [World Table Tennis Championships, formerFrequencyChangeYear, 1957]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: formerFrequencyChangeYear Context triple: [World Table Tennis Championships, formerFrequencyChangeYear, 1957]
-
A.
frequencyInHistory
Indicates how often a particular event, state, or relationship has occurred over time within a given historical context.
-
B.
frequencyChange
Indicates a change in how often an event, action, or state occurs over time.
-
C.
replacedEachYear
Indicates that one entity is substituted or exchanged for another on a yearly basis.
-
D.
replacedFrequency
Indicates how often one entity is substituted for or takes the place of another over a given period.
-
E.
transitionYear
chosen
Indicates the specific year in which a change, shift, or transition from one state, condition, or phase to another occurs.
- 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_69d87f2950248190bc8ad9b9bebdc8c8 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e327d1f16481909adb19dab86dcc72 |
completed | April 18, 2026, 6:42 a.m. |
| PD | Predicate disambiguation | batch_69e226fe1dd08190865c181721f8c348 |
completed | April 17, 2026, 12:26 p.m. |
Created at: April 10, 2026, 5:09 a.m.