Triple
T12399679
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fresno FC |
E296216
|
entity |
| Predicate | seasonCountInUSLChampionship |
P104633
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [Fresno FC, seasonCountInUSLChampionship, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: seasonCountInUSLChampionship Context triple: [Fresno FC, seasonCountInUSLChampionship, 2]
-
A.
numberOfUSLChampionshipClubsEntered
Indicates the quantity of clubs that have participated in the USL Championship associated with a given entity or event.
-
B.
seasonCountInNASL
Indicates the number of seasons an entity participated in the NASL (North American Soccer League).
-
C.
numberOfUSLSecondDivisionClubsEntered
Indicates the number of clubs that participated in the USL Second Division.
-
D.
joinedUSLChampionship
Indicates that an entity became a member or participant in the USL Championship league.
-
E.
numberOfUSLFirstDivisionClubsEntered
Indicates the number of clubs a subject has entered into the USL First 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_69d6ad9f464c81909db36d7e96e34b9e |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d9401cbfd481908ee6e765da3d12cb |
completed | April 10, 2026, 6:23 p.m. |
| PD | Predicate disambiguation | batch_69d93ed4cea08190ad374d3f6a798053 |
completed | April 10, 2026, 6:17 p.m. |
| PDg | Predicate description generation | batch_69d93f607a88819089e89fd263ae9937 |
completed | April 10, 2026, 6:20 p.m. |
Created at: April 8, 2026, 9:55 p.m.