Triple
T1746491
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michelle Kwan |
E38346
|
entity |
| Predicate | USNationalTitlesCount |
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, USNationalTitlesCount, 9]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: USNationalTitlesCount Context triple: [Michelle Kwan, USNationalTitlesCount, 9]
-
A.
winnerTitleCount
chosen
Indicates the number of titles or championships an entity has won.
-
B.
nationalChampionshipTitle
Indicates that an entity has won a national-level championship title in a particular sport, competition, or field.
-
C.
mastersTitles
Indicates that one entity holds one or more master's degree titles associated with another entity (such as an institution, field, or program).
-
D.
worldChampionshipTitles
Indicates the number of world championship titles an entity has won.
-
E.
hasClaimedNationalTitlesInEra
Indicates that an entity has won or been awarded national titles during a specified historical period or era.
- 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_69a8862b01a48190ab47209063af82d9 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69ab630e7d008190a8c673665d9672bb |
completed | March 6, 2026, 11:28 p.m. |
| PD | Predicate disambiguation | batch_69aa61c5a18481909bc49e0c54d64314 |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:31 p.m.