Triple
T6810692
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Federal League |
E156623
|
entity |
| Predicate | playerRelations |
P73215
|
FINISHED |
| Object | challenged reserve clause practices |
—
|
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: challenged reserve clause practices | Statement: [Federal League, playerRelations, challenged reserve clause practices]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: playerRelations Context triple: [Federal League, playerRelations, challenged reserve clause practices]
-
A.
relationshipToCharacter
Indicates the specific type of personal, social, or narrative connection that one entity has to a given character.
-
B.
inRelationshipWith
Indicates that two entities are mutually involved in a defined personal, romantic, or partnership relationship with each other.
-
C.
reportsRelationship
Indicates that one entity formally provides information, findings, or status about another entity or situation.
-
D.
relationshipPlannedWith
Indicates that a relationship between two entities has been intentionally arranged or scheduled to occur in the future.
-
E.
characterActorRelationship
Indicates a relationship where an actor portrays or is associated with a specific character in a work.
- 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_69c68828b26c819090fe9df7612bbc27 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d30ded6481908fd64611607c610e |
completed | March 27, 2026, 6:57 p.m. |
| PD | Predicate disambiguation | batch_69c6d09bb4f881909bf20c188cb3e8e1 |
completed | March 27, 2026, 6:46 p.m. |
| PDg | Predicate description generation | batch_69c6d1d5f1908190989efc8a2d18c965 |
completed | March 27, 2026, 6:52 p.m. |
Created at: March 27, 2026, 2:16 p.m.