Triple
T15298861
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | International Table Tennis Federation |
E365731
|
entity |
| Predicate | changedBallMaterialChangeEffectiveYear |
P23631
|
FINISHED |
| Object | 2014 |
—
|
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: 2014 | Statement: [International Table Tennis Federation, changedBallMaterialChangeEffectiveYear, 2014]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: changedBallMaterialChangeEffectiveYear Context triple: [International Table Tennis Federation, changedBallMaterialChangeEffectiveYear, 2014]
-
A.
replacedInYear
Indicates that one entity took the place of or superseded another entity in a specific calendar year.
-
B.
reversionYear
Indicates the year in which something returns to a previous state, condition, or ownership.
-
C.
redesignationYear
Indicates the year in which something was officially redesignated, renamed, or assigned a new status or classification.
-
D.
effectiveYear
chosen
Indicates the calendar year in which something (such as a rule, status, or agreement) becomes valid or takes effect.
-
E.
banYear
Indicates the year in which a ban was enacted or came into effect on the related entity or activity.
- 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_69d85a113ee881908e297a1d38dd79fa |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03686bfb8819080ba0caae652170a |
completed | April 16, 2026, 1:08 a.m. |
| PD | Predicate disambiguation | batch_69deca935e2c8190b640987ddfc542b9 |
completed | April 14, 2026, 11:15 p.m. |
Created at: April 10, 2026, 3:15 a.m.