Triple
T19146744
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North Carolina Tar Heels women's soccer |
E468697
|
entity |
| Predicate | hasWonNCAAWomen'sSoccerChampionships |
P24536
|
FINISHED |
| Object | more than 20 |
—
|
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: more than 20 | Statement: [North Carolina Tar Heels women's soccer, hasWonNCAAWomen'sSoccerChampionships, more than 20]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWonNCAAWomen'sSoccerChampionships Context triple: [North Carolina Tar Heels women's soccer, hasWonNCAAWomen'sSoccerChampionships, more than 20]
-
A.
womenSoccerNCAATitleSeason
Indicates that the subject entity won the NCAA women’s soccer championship in the specified season.
-
B.
championSchoolFirstNCAAWomenTitle
Indicates that a school won its first NCAA women’s championship title in a given sport or event.
-
C.
wonNCAAWomenCollegeWorldSeriesTitle
Indicates that one entity secured the championship title in the NCAA Women's College World Series.
-
D.
hasWonNCAATitleIn
Indicates that an entity has won an NCAA championship title in a specified sport, category, or year.
-
E.
NCAAChampionshipCount
chosen
Indicates the number of NCAA championships 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_69d8dd084ff48190ac0f8c46ee722629 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e9796ebc8190928f4b227685bc33 |
completed | April 20, 2026, 8:53 a.m. |
| PD | Predicate disambiguation | batch_69e4b9b475d88190a8c15e8eb01dbfef |
completed | April 19, 2026, 11:17 a.m. |
Created at: April 10, 2026, 12:06 p.m.