Triple
T6674110
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tod Leiweke |
E151805
|
entity |
| Predicate | sportIndustry |
P71678
|
FINISHED |
| Object | ice hockey |
—
|
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: ice hockey | Statement: [Tod Leiweke, sportIndustry, ice hockey]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sportIndustry Context triple: [Tod Leiweke, sportIndustry, ice hockey]
-
A.
otherSportIndustry
Indicates a relationship where an entity is involved in, associated with, or belongs to a sports-related industry other than the primary or specified one.
-
B.
sport
Indicates that an entity participates in, is associated with, or is characterized by a particular athletic activity or game.
-
C.
sportsBrand
Indicates that one entity is a sports-related brand or label associated with the other entity.
-
D.
sportCategory
Indicates that one entity is classified as a type or category of sport to which the other entity (typically a specific sport or sporting event) belongs.
-
E.
sportsName
Indicates the specific sport associated with or played in a given context or event.
- 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_69c687f830bc81909eb8b04dbb8450b1 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6c0aa8c5c8190a302b261f11b70cb |
completed | March 27, 2026, 5:38 p.m. |
| PD | Predicate disambiguation | batch_69c6ad0b6d00819086205b8ce30dd045 |
completed | March 27, 2026, 4:15 p.m. |
| PDg | Predicate description generation | batch_69c6c0a90a088190978061cb05dbe268 |
completed | March 27, 2026, 5:38 p.m. |
Created at: March 27, 2026, 2:03 p.m.