Triple
T10947556
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | U.S. Open Cup 2023 |
E258636
|
entity |
| Predicate | numberOfUSLLeagueOneClubsEntered |
P96780
|
FINISHED |
| Object | 11 |
—
|
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: 11 | Statement: [U.S. Open Cup 2023, numberOfUSLLeagueOneClubsEntered, 11]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfUSLLeagueOneClubsEntered Context triple: [U.S. Open Cup 2023, numberOfUSLLeagueOneClubsEntered, 11]
-
A.
numberOfUSLFirstDivisionClubsEntered
Indicates the number of clubs a subject has entered into the USL First Division.
-
B.
numberOfUSLSecondDivisionClubsEntered
Indicates the number of clubs that participated in the USL Second Division.
-
C.
numberOfUSASAClubsEntered
Indicates the count of USASA clubs that a given entity has entered or participated in.
-
D.
numberOfPDLClubsEntered
Indicates the count of PDL clubs that an entity has entered or participated in.
-
E.
numberOfLeagues
Indicates the quantity of leagues associated with or attributed to a given entity or relationship.
- 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_69d6aa8769b4819082bfe5e61b9017f0 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d770ebac3c8190849ddda3d9d37327 |
completed | April 9, 2026, 9:27 a.m. |
| PD | Predicate disambiguation | batch_69d72e816a98819096d6c10dfb88a66a |
completed | April 9, 2026, 4:43 a.m. |
| PDg | Predicate description generation | batch_69d7322370648190ba14cdd6fb4cdcb0 |
completed | April 9, 2026, 4:59 a.m. |
Created at: April 8, 2026, 9:23 p.m.