Triple
T33566690
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Skaggs |
E859778
|
entity |
| Predicate | hasNotableSportsBearer |
P163862
|
FINISHED |
| Object | Tyler Skaggs |
E2057971
|
NE 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: Tyler Skaggs | Statement: [Skaggs, hasNotableSportsBearer, Tyler Skaggs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableSportsBearer Context triple: [Skaggs, hasNotableSportsBearer, Tyler Skaggs]
-
A.
hasAthlete
Indicates a relationship where an entity (such as a team, organization, or event) includes or is associated with one or more athletes.
-
B.
hasNotableSportAssociation
Indicates a relationship where an entity is significantly connected to, recognized for, or prominently involved with a particular sport or sports organization.
-
C.
hasSportsRole
Indicates that an entity holds or is assigned a specific role or position within a sports context or organization.
-
D.
hasAssociatedSportFigure
chosen
Indicates that an entity is linked or related to a particular sports figure (such as an athlete, coach, or sports personality).
-
E.
hasSportsStatus
Indicates that an entity holds a particular sports-related status, role, or classification (such as amateur, professional, active, or retired) within a sporting context.
- F. None of above.
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_69f3497c1d288190a844ea699914e038 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a01c5c5dbb881909b19ba87a7760ee7 |
completed | May 11, 2026, 12:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a36118c42648190a7f1a54d7893340b |
completed | June 20, 2026, 4:05 a.m. |
| PD | Predicate disambiguation | batch_6a01c549af98819098e0effd775b7710 |
completed | May 11, 2026, 12:02 p.m. |
Created at: May 1, 2026, 1:40 a.m.