Triple
T5473316
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | U.S. Open Cup 2010 |
E122887
|
entity |
| Predicate | numberOfMajorLeagueSoccerTeams |
P63958
|
FINISHED |
| Object | 8 |
—
|
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: 8 | Statement: [U.S. Open Cup 2010, numberOfMajorLeagueSoccerTeams, 8]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfMajorLeagueSoccerTeams Context triple: [U.S. Open Cup 2010, numberOfMajorLeagueSoccerTeams, 8]
-
A.
numberOfTeamsInUnitedStates
Indicates the total count of teams that are located within or belong to the United States.
-
B.
majorLeagueSoccerClubHosted
Indicates that a Major League Soccer club served as the host team or venue for a particular match, event, or opponent.
-
C.
numberOfLeagues
Indicates the quantity of leagues associated with or attributed to a given entity or relationship.
-
D.
numberOfUSLFirstDivisionClubsEntered
Indicates the number of clubs a subject has entered into the USL First Division.
-
E.
numberOfUSLSecondDivisionClubsEntered
Indicates the number of clubs that participated in the USL Second Division.
- 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_69bd46459ff48190823377457bcf7128 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd9230d6d88190a9ac48a4488e1754 |
completed | March 20, 2026, 6:30 p.m. |
| PD | Predicate disambiguation | batch_69bd91a58c448190904964a439045e05 |
completed | March 20, 2026, 6:27 p.m. |
| PDg | Predicate description generation | batch_69bd9214b8488190979112c7615f359a |
completed | March 20, 2026, 6:29 p.m. |
Created at: March 20, 2026, 2:09 p.m.