Triple
T20231563
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boris Becker |
E495537
|
entity |
| Predicate | wonAustralianOpenSinglesYear |
P139328
|
FINISHED |
| Object | 1991 |
—
|
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: 1991 | Statement: [Boris Becker, wonAustralianOpenSinglesYear, 1991]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wonAustralianOpenSinglesYear Context triple: [Boris Becker, wonAustralianOpenSinglesYear, 1991]
-
A.
australianOpenSinglesTitles
Indicates the number of Australian Open singles titles one entity has won.
-
B.
wonWimbledonSingles
Indicates that an entity has won the Wimbledon tennis tournament in the singles category.
-
C.
grandSlamBestResultAustralianOpen
Indicates the best performance or highest round an entity has achieved specifically at the Australian Open in Grand Slam competition.
-
D.
grandSlamSinglesFinalYear
Indicates the year in which a given Grand Slam singles final match took place.
-
E.
wonUSOpen
Indicates that one entity achieved victory in the US Open competition or tournament over another entity or in a given year.
- 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_69da626cff80819097b530718a7c98b6 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66fddafac819089cef4158f5e0ab5 |
completed | April 20, 2026, 6:26 p.m. |
| PD | Predicate disambiguation | batch_69e55b18609481909ab28bc8750a642f |
completed | April 19, 2026, 10:45 p.m. |
| PDg | Predicate description generation | batch_69e56702ad04819099c1c08f28d16809 |
completed | April 19, 2026, 11:36 p.m. |
Created at: April 11, 2026, 11:39 p.m.