Triple
T8209782
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | San Antonio Scorpions |
E191783
|
entity |
| Predicate | majorTrophyCount |
P66411
|
FINISHED |
| Object | 1 NASL championship |
—
|
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: 1 NASL championship | Statement: [San Antonio Scorpions, majorTrophyCount, 1 NASL championship]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: majorTrophyCount Context triple: [San Antonio Scorpions, majorTrophyCount, 1 NASL championship]
-
A.
trophyCount
chosen
Indicates the number of trophies associated with a given entity.
-
B.
hasTrophyStatus
Indicates that an entity possesses a particular trophy-related status or classification.
-
C.
trophy
Indicates that one entity is a trophy awarded or possessed in relation to another entity, typically as a result of winning or achieving something.
-
D.
numberOfVezinaTrophies
Indicates the count of Vezina Trophies that an entity (typically an ice hockey goaltender) has been awarded.
-
E.
trophyOfficialName
Indicates the official, formally recognized name assigned to a particular trophy.
- 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_69ca82c8c054819087fedd9a5436b8a3 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb76dc784881908e1f63ac907cdd01 |
completed | March 31, 2026, 7:25 a.m. |
| PD | Predicate disambiguation | batch_69cb36ad01ac81909609b15f6a6c8581 |
completed | March 31, 2026, 2:51 a.m. |
Created at: March 30, 2026, 5:44 p.m.