Triple
T25220420
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Margaret Court |
E631945
|
entity |
| Predicate | yearOfCalendarGrandSlamSingles |
P158567
|
FINISHED |
| Object | 1970 |
—
|
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: 1970 | Statement: [Margaret Court, yearOfCalendarGrandSlamSingles, 1970]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: yearOfCalendarGrandSlamSingles Context triple: [Margaret Court, yearOfCalendarGrandSlamSingles, 1970]
-
A.
yearOfGrandSlam
Indicates the specific year in which a particular Grand Slam event or achievement took place.
-
B.
grandSlamSinglesFinalYear
Indicates the year in which a given Grand Slam singles final match took place.
-
C.
bestGrandSlamResultYear
Indicates the year in which an entity achieved its best (highest) Grand Slam tournament result.
-
D.
calendarYearGrandSlamContext
chosen
Indicates the context in which an entity achieves or is associated with winning all four major championships within the same calendar year.
-
E.
grandSlamSinglesTitles
Indicates the number of Grand Slam singles tennis titles an entity has won.
- 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_69e75a8e0f688190a7aebe9a4815e25b |
completed | April 21, 2026, 11:07 a.m. |
| NER | Named-entity recognition | batch_69f62d89b89c8190afb372a8172111e7 |
completed | May 2, 2026, 4:59 p.m. |
| PD | Predicate disambiguation | batch_69f62c1379f08190836c3e02b0c892df |
completed | May 2, 2026, 4:53 p.m. |
Created at: April 21, 2026, 1:03 p.m.