Triple
T32934544
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Goh Liu Ying |
E842490
|
entity |
| Predicate | notablePartnerInMixedDoubles |
P205205
|
FINISHED |
| Object | Chan Peng Soon |
E848140
|
NE 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: Chan Peng Soon | Statement: [Goh Liu Ying, notablePartnerInMixedDoubles, Chan Peng Soon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notablePartnerInMixedDoubles Context triple: [Goh Liu Ying, notablePartnerInMixedDoubles, Chan Peng Soon]
-
A.
mixedDoublesChampions
Indicates that the related entities together won a mixed doubles championship in a given event or competition.
-
B.
grandSlamMixedDoublesTitles
Indicates the number of Grand Slam tennis titles an entity has won in mixed doubles events.
-
C.
hasMixedDoublesEquivalent
Indicates that one entity corresponds to or serves as the mixed doubles counterpart or equivalent of another entity.
-
D.
AustralianOpenDoublesChampion
Indicates that the subject is the winner of the doubles competition at the Australian Open tennis tournament for a given year.
-
E.
WimbledonDoublesChampion
Indicates that the subject has won the doubles championship title at the Wimbledon tennis tournament.
- F. None of above. chosen
Provenance (5 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_69f34948adfc8190a937f1f622783c0b |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a037cad051c8190b28b354b89208574 |
completed | May 12, 2026, 7:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a34e4fa71f081908fd6c4220525a9fd |
completed | June 19, 2026, 6:43 a.m. |
| PD | Predicate disambiguation | batch_6a0379f0cbe481909b4b8fc6cbe297f0 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037cab06288190b093935f235ddff2 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 1, 2026, 1:20 a.m.