Triple
T8382611
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michelle Kwan |
E197729
|
entity |
| Predicate | hasUSNationalTitlesCount |
P25122
|
FINISHED |
| Object | 9 |
—
|
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: 9 | Statement: [Michelle Kwan, hasUSNationalTitlesCount, 9]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUSNationalTitlesCount Context triple: [Michelle Kwan, hasUSNationalTitlesCount, 9]
-
A.
hasClaimedNationalTitlesInEra
Indicates that an entity has won or been awarded national titles during a specified historical period or era.
-
B.
winnerTitleCount
chosen
Indicates the number of titles or championships an entity has won.
-
C.
numberOfTitleDefenses
Indicates the number of times an entity has successfully defended a previously won title or championship.
-
D.
nationalTeamTitleCount
Indicates the number of titles or championships a national team has won.
-
E.
mastersTitles
Indicates that one entity holds one or more master's degree titles associated with another entity (such as an institution, field, or program).
- 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_69ca82f64c188190af4e1608036b865d |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb80ddc0f08190a90d4d9070bf713b |
completed | March 31, 2026, 8:07 a.m. |
| PD | Predicate disambiguation | batch_69cb70cfe82881909fe374ba52649e84 |
completed | March 31, 2026, 6:59 a.m. |
Created at: March 30, 2026, 6:02 p.m.